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A Closer Look at Spatiotemporal Convolutions for Action Recognition
| 2,480
|
cvpr
| 162
| 28
|
2023-06-03 02:03:24.133000
|
https://github.com/facebookresearch/R2Plus1D
| 1,020
|
A closer look at spatiotemporal convolutions for action recognition
|
https://scholar.google.com/scholar?cluster=9524036545693727210&hl=en&as_sdt=0,33
| 111
| 2,018
|
SurfConv: Bridging 3D and 2D Convolution for RGBD Images
| 22
|
cvpr
| 6
| 0
|
2023-06-03 02:03:24.333000
|
https://github.com/chuhang/SurfConv
| 53
|
Surfconv: Bridging 3d and 2d convolution for rgbd images
|
https://scholar.google.com/scholar?cluster=7050444684028736511&hl=en&as_sdt=0,33
| 4
| 2,018
|
Efficient Video Object Segmentation via Network Modulation
| 344
|
cvpr
| 24
| 5
|
2023-06-03 02:03:24.532000
|
https://github.com/linjieyangsc/video_seg
| 152
|
Efficient video object segmentation via network modulation
|
https://scholar.google.com/scholar?cluster=1976126252599424631&hl=en&as_sdt=0,33
| 7
| 2,018
|
Weakly-Supervised Action Segmentation With Iterative Soft Boundary Assignment
| 170
|
cvpr
| 12
| 1
|
2023-06-03 02:03:24.732000
|
https://github.com/ld-ing/TCFPN-ISBA
| 40
|
Weakly-supervised action segmentation with iterative soft boundary assignment
|
https://scholar.google.com/scholar?cluster=8585781658332698642&hl=en&as_sdt=0,44
| 4
| 2,018
|
Can Spatiotemporal 3D CNNs Retrace the History of 2D CNNs and ImageNet?
| 1,749
|
cvpr
| 911
| 153
|
2023-06-03 02:03:24.932000
|
https://github.com/kenshohara/3D-ResNets-PyTorch
| 3,611
|
Can spatiotemporal 3d cnns retrace the history of 2d cnns and imagenet?
|
https://scholar.google.com/scholar?cluster=4579944187863414163&hl=en&as_sdt=0,22
| 59
| 2,018
|
PiCANet: Learning Pixel-Wise Contextual Attention for Saliency Detection
| 759
|
cvpr
| 16
| 0
|
2023-06-03 02:03:25.132000
|
https://github.com/nian-liu/PiCANet
| 34
|
Picanet: Learning pixel-wise contextual attention for saliency detection
|
https://scholar.google.com/scholar?cluster=10105062679755015166&hl=en&as_sdt=0,5
| 5
| 2,018
|
What Do Deep Networks Like to See?
| 36
|
cvpr
| 3
| 0
|
2023-06-03 02:03:25.333000
|
https://github.com/spalaciob/s2snets-reconstruction
| 14
|
What do deep networks like to see?
|
https://scholar.google.com/scholar?cluster=5407091813991175051&hl=en&as_sdt=0,33
| 2
| 2,018
|
Multi-Frame Quality Enhancement for Compressed Video
| 194
|
cvpr
| 21
| 2
|
2023-06-03 02:03:25.532000
|
https://github.com/ryangBUAA/MFQE
| 92
|
Multi-frame quality enhancement for compressed video
|
https://scholar.google.com/scholar?cluster=13441933018643229678&hl=en&as_sdt=0,5
| 6
| 2,018
|
Active Fixation Control to Predict Saccade Sequences
| 41
|
cvpr
| 1
| 1
|
2023-06-03 02:03:25.732000
|
https://github.com/TsotsosLab/STAR-FC
| 16
|
Active fixation control to predict saccade sequences
|
https://scholar.google.com/scholar?cluster=5313953482186601173&hl=en&as_sdt=0,14
| 8
| 2,018
|
Latent RANSAC
| 30
|
cvpr
| 10
| 0
|
2023-06-03 02:03:25.932000
|
https://github.com/rlit/LatentRANSAC
| 23
|
Latent ransac
|
https://scholar.google.com/scholar?cluster=16432006796453756987&hl=en&as_sdt=0,47
| 8
| 2,018
|
Deep Video Super-Resolution Network Using Dynamic Upsampling Filters Without Explicit Motion Compensation
| 476
|
cvpr
| 50
| 11
|
2023-06-03 02:03:26.133000
|
https://github.com/yhjo09/VSR-DUF
| 217
|
Deep video super-resolution network using dynamic upsampling filters without explicit motion compensation
|
https://scholar.google.com/scholar?cluster=14547343431451944570&hl=en&as_sdt=0,1
| 10
| 2,018
|
Learning a Single Convolutional Super-Resolution Network for Multiple Degradations
| 860
|
cvpr
| 78
| 19
|
2023-06-03 02:03:26.333000
|
https://github.com/cszn/SRMD
| 403
|
Learning a single convolutional super-resolution network for multiple degradations
|
https://scholar.google.com/scholar?cluster=12748399699451058322&hl=en&as_sdt=0,5
| 13
| 2,018
|
FFNet: Video Fast-Forwarding via Reinforcement Learning
| 53
|
cvpr
| 4
| 1
|
2023-06-03 02:03:26.534000
|
https://github.com/shuyueL/FFNet
| 20
|
Ffnet: Video fast-forwarding via reinforcement learning
|
https://scholar.google.com/scholar?cluster=12600528794155457319&hl=en&as_sdt=0,34
| 1
| 2,018
|
Domain Adaptive Faster R-CNN for Object Detection in the Wild
| 1,042
|
cvpr
| 69
| 13
|
2023-06-03 02:03:26.734000
|
https://github.com/yuhuayc/da-faster-rcnn
| 320
|
Domain adaptive faster r-cnn for object detection in the wild
|
https://scholar.google.com/scholar?cluster=2169991804006218555&hl=en&as_sdt=0,5
| 11
| 2,018
|
Low-Shot Learning With Large-Scale Diffusion
| 116
|
cvpr
| 5
| 0
|
2023-06-03 02:03:26.935000
|
https://github.com/facebookresearch/low-shot-with-diffusion
| 47
|
Low-shot learning with large-scale diffusion
|
https://scholar.google.com/scholar?cluster=18181091707667282501&hl=en&as_sdt=0,5
| 7
| 2,018
|
Referring Relationships
| 94
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cvpr
| 81
| 10
|
2023-06-03 02:03:27.136000
|
https://github.com/StanfordVL/ReferringRelationships
| 262
|
Referring relationships
|
https://scholar.google.com/scholar?cluster=6942937541363789656&hl=en&as_sdt=0,33
| 19
| 2,018
|
Adversarially Learned One-Class Classifier for Novelty Detection
| 617
|
cvpr
| 77
| 0
|
2023-06-03 02:03:27.336000
|
https://github.com/khalooei/ALOCC-CVPR2018
| 204
|
Adversarially learned one-class classifier for novelty detection
|
https://scholar.google.com/scholar?cluster=13603058643518336613&hl=en&as_sdt=0,48
| 16
| 2,018
|
Improving Object Localization With Fitness NMS and Bounded IoU Loss
| 189
|
cvpr
| 29
| 4
|
2023-06-03 02:03:27.537000
|
https://github.com/lachlants/denet
| 112
|
Improving object localization with fitness nms and bounded iou loss
|
https://scholar.google.com/scholar?cluster=10163124065967812010&hl=en&as_sdt=0,10
| 11
| 2,018
|
End-to-End Deep Kronecker-Product Matching for Person Re-Identification
| 148
|
cvpr
| 29
| 1
|
2023-06-03 02:03:27.739000
|
https://github.com/YantaoShen/kpm_rw_person_reid
| 103
|
End-to-end deep kronecker-product matching for person re-identification
|
https://scholar.google.com/scholar?cluster=4096787433309580582&hl=en&as_sdt=0,5
| 6
| 2,018
|
Deformable GANs for Pose-Based Human Image Generation
| 443
|
cvpr
| 81
| 21
|
2023-06-03 02:03:27.940000
|
https://github.com/AliaksandrSiarohin/pose-gan
| 373
|
Deformable gans for pose-based human image generation
|
https://scholar.google.com/scholar?cluster=3043558815618961635&hl=en&as_sdt=0,5
| 18
| 2,018
|
Deep Reinforcement Learning of Region Proposal Networks for Object Detection
| 73
|
cvpr
| 19
| 0
|
2023-06-03 02:03:28.139000
|
https://github.com/aleksispi/drl-rpn-tf
| 72
|
Deep reinforcement learning of region proposal networks for object detection
|
https://scholar.google.com/scholar?cluster=5027202690407581149&hl=en&as_sdt=0,5
| 6
| 2,018
|
Discriminability Objective for Training Descriptive Captions
| 189
|
cvpr
| 22
| 7
|
2023-06-03 02:03:28.340000
|
https://github.com/ruotianluo/DiscCaptioning
| 110
|
Discriminability objective for training descriptive captions
|
https://scholar.google.com/scholar?cluster=4573642077602787213&hl=en&as_sdt=0,10
| 6
| 2,018
|
Robust Classification With Convolutional Prototype Learning
| 227
|
cvpr
| 32
| 4
|
2023-06-03 02:03:28.540000
|
https://github.com/YangHM/Convolutional-Prototype-Learning
| 117
|
Robust classification with convolutional prototype learning
|
https://scholar.google.com/scholar?cluster=15165539618467322604&hl=en&as_sdt=0,44
| 7
| 2,018
|
Generative Modeling Using the Sliced Wasserstein Distance
| 190
|
cvpr
| 3
| 2
|
2023-06-03 02:03:28.740000
|
https://github.com/ishansd/swg
| 33
|
Generative modeling using the sliced wasserstein distance
|
https://scholar.google.com/scholar?cluster=16060361472863218540&hl=en&as_sdt=0,44
| 4
| 2,018
|
Learning Time/Memory-Efficient Deep Architectures With Budgeted Super Networks
| 96
|
cvpr
| 5
| 0
|
2023-06-03 02:03:28.941000
|
https://github.com/TomVeniat/bsn
| 26
|
Learning time/memory-efficient deep architectures with budgeted super networks
|
https://scholar.google.com/scholar?cluster=5514870632955712695&hl=en&as_sdt=0,33
| 3
| 2,018
|
Cross-View Image Synthesis Using Conditional GANs
| 153
|
cvpr
| 11
| 8
|
2023-06-03 02:03:29.141000
|
https://github.com/kregmi/cross-view-image-synthesis
| 50
|
Cross-view image synthesis using conditional gans
|
https://scholar.google.com/scholar?cluster=15120435124755343968&hl=en&as_sdt=0,34
| 4
| 2,018
|
Weakly-Supervised Semantic Segmentation Network With Deep Seeded Region Growing
| 516
|
cvpr
| 36
| 15
|
2023-06-03 02:03:29.340000
|
https://github.com/speedinghzl/DSRG
| 245
|
Weakly-supervised semantic segmentation network with deep seeded region growing
|
https://scholar.google.com/scholar?cluster=11401463134094123362&hl=en&as_sdt=0,39
| 12
| 2,018
|
Deep Spatial Feature Reconstruction for Partial Person Re-Identification: Alignment-Free Approach
| 265
|
cvpr
| 31
| 9
|
2023-06-03 02:03:29.541000
|
https://github.com/lingxiao-he/Partial-Person-ReID
| 160
|
Deep spatial feature reconstruction for partial person re-identification: Alignment-free approach
|
https://scholar.google.com/scholar?cluster=16383414441740542927&hl=en&as_sdt=0,5
| 7
| 2,018
|
Cascaded Pyramid Network for Multi-Person Pose Estimation
| 1,245
|
cvpr
| 201
| 43
|
2023-06-03 02:03:29.743000
|
https://github.com/chenyilun95/tf-cpn
| 788
|
Cascaded pyramid network for multi-person pose estimation
|
https://scholar.google.com/scholar?cluster=5670760275903596839&hl=en&as_sdt=0,33
| 27
| 2,018
|
Finding Task-Relevant Features for Few-Shot Learning by Category Traversal
| 324
|
cvpr
| 31
| 6
|
2023-06-03 02:17:46.966000
|
https://github.com/Clarifai/few-shot-ctm
| 152
|
Finding task-relevant features for few-shot learning by category traversal
|
https://scholar.google.com/scholar?cluster=7690321196923369761&hl=en&as_sdt=0,5
| 25
| 2,019
|
Edge-Labeling Graph Neural Network for Few-Shot Learning
| 442
|
cvpr
| 65
| 21
|
2023-06-03 02:17:47.165000
|
https://github.com/khy0809/fewshot-egnn
| 260
|
Edge-labeling graph neural network for few-shot learning
|
https://scholar.google.com/scholar?cluster=8574108187034418609&hl=en&as_sdt=0,36
| 6
| 2,019
|
Learning Video Representations From Correspondence Proposals
| 66
|
cvpr
| 12
| 1
|
2023-06-03 02:17:47.364000
|
https://github.com/xingyul/cpnet
| 93
|
Learning video representations from correspondence proposals
|
https://scholar.google.com/scholar?cluster=7665702673430883055&hl=en&as_sdt=0,34
| 1
| 2,019
|
Holistic and Comprehensive Annotation of Clinically Significant Findings on Diverse CT Images: Learning From Radiology Reports and Label Ontology
| 57
|
cvpr
| 188
| 17
|
2023-06-03 02:17:47.564000
|
https://github.com/rsummers11/CADLab
| 409
|
Holistic and comprehensive annotation of clinically significant findings on diverse CT images: learning from radiology reports and label ontology
|
https://scholar.google.com/scholar?cluster=6878217630382772571&hl=en&as_sdt=0,6
| 29
| 2,019
|
Generating Classification Weights With GNN Denoising Autoencoders for Few-Shot Learning
| 251
|
cvpr
| 21
| 12
|
2023-06-03 02:17:47.764000
|
https://github.com/gidariss/wDAE_GNN_FewShot
| 148
|
Generating classification weights with gnn denoising autoencoders for few-shot learning
|
https://scholar.google.com/scholar?cluster=13700723211966973086&hl=en&as_sdt=0,5
| 13
| 2,019
|
Kervolutional Neural Networks
| 74
|
cvpr
| 3
| 4
|
2023-06-03 02:17:47.964000
|
https://github.com/wang-chen/kervolution
| 37
|
Kervolutional neural networks
|
https://scholar.google.com/scholar?cluster=11581113643161028532&hl=en&as_sdt=0,33
| 7
| 2,019
|
Sphere Generative Adversarial Network Based on Geometric Moment Matching
| 38
|
cvpr
| 4
| 1
|
2023-06-03 02:17:48.164000
|
https://github.com/pswkiki/SphereGAN
| 14
|
Sphere generative adversarial network based on geometric moment matching
|
https://scholar.google.com/scholar?cluster=7334963438871902572&hl=en&as_sdt=0,33
| 0
| 2,019
|
Data Augmentation Using Learned Transformations for One-Shot Medical Image Segmentation
| 399
|
cvpr
| 93
| 10
|
2023-06-03 02:17:48.363000
|
https://github.com/xamyzhao/brainstorm
| 389
|
Data augmentation using learned transformations for one-shot medical image segmentation
|
https://scholar.google.com/scholar?cluster=15710438805315912771&hl=en&as_sdt=0,6
| 12
| 2,019
|
Why ReLU Networks Yield High-Confidence Predictions Far Away From the Training Data and How to Mitigate the Problem
| 409
|
cvpr
| 21
| 1
|
2023-06-03 02:17:48.563000
|
https://github.com/max-andr/relu_networks_overconfident
| 181
|
Why relu networks yield high-confidence predictions far away from the training data and how to mitigate the problem
|
https://scholar.google.com/scholar?cluster=1495531200128833945&hl=en&as_sdt=0,1
| 6
| 2,019
|
Evading Defenses to Transferable Adversarial Examples by Translation-Invariant Attacks
| 505
|
cvpr
| 22
| 4
|
2023-06-03 02:17:48.763000
|
https://github.com/dongyp13/Translation-Invariant-Attacks
| 124
|
Evading defenses to transferable adversarial examples by translation-invariant attacks
|
https://scholar.google.com/scholar?cluster=165426210106722967&hl=en&as_sdt=0,33
| 3
| 2,019
|
Hardness-Aware Deep Metric Learning
| 176
|
cvpr
| 29
| 6
|
2023-06-03 02:17:48.963000
|
https://github.com/wzzheng/HDML
| 149
|
Hardness-aware deep metric learning
|
https://scholar.google.com/scholar?cluster=8375662549135355127&hl=en&as_sdt=0,33
| 4
| 2,019
|
Auto-DeepLab: Hierarchical Neural Architecture Search for Semantic Image Segmentation
| 969
|
cvpr
| 46,274
| 1,204
|
2023-06-03 02:17:49.162000
|
https://github.com/tensorflow/models
| 75,883
|
Auto-deeplab: Hierarchical neural architecture search for semantic image segmentation
|
https://scholar.google.com/scholar?cluster=548023770660590636&hl=en&as_sdt=0,14
| 2,774
| 2,019
|
Filter Pruning via Geometric Median for Deep Convolutional Neural Networks Acceleration
| 956
|
cvpr
| 107
| 12
|
2023-06-03 02:17:49.362000
|
https://github.com/he-y/filter-pruning-geometric-median
| 477
|
Filter pruning via geometric median for deep convolutional neural networks acceleration
|
https://scholar.google.com/scholar?cluster=3978996322124428221&hl=en&as_sdt=0,22
| 7
| 2,019
|
Content Authentication for Neural Imaging Pipelines: End-To-End Optimization of Photo Provenance in Complex Distribution Channels
| 13
|
cvpr
| 30
| 4
|
2023-06-03 02:17:49.561000
|
https://github.com/pkorus/neural-imaging
| 136
|
Content authentication for neural imaging pipelines: End-to-end optimization of photo provenance in complex distribution channels
|
https://scholar.google.com/scholar?cluster=11213241954859682918&hl=en&as_sdt=0,5
| 11
| 2,019
|
DeepMapping: Unsupervised Map Estimation From Multiple Point Clouds
| 60
|
cvpr
| 46
| 0
|
2023-06-03 02:17:49.761000
|
https://github.com/ai4ce/DeepMapping
| 190
|
DeepMapping: Unsupervised map estimation from multiple point clouds
|
https://scholar.google.com/scholar?cluster=9988954344653969501&hl=en&as_sdt=0,11
| 21
| 2,019
|
3D-SIS: 3D Semantic Instance Segmentation of RGB-D Scans
| 359
|
cvpr
| 75
| 13
|
2023-06-03 02:17:49.961000
|
https://github.com/Sekunde/3D-SIS
| 360
|
3d-sis: 3d semantic instance segmentation of rgb-d scans
|
https://scholar.google.com/scholar?cluster=18028162509439004162&hl=en&as_sdt=0,45
| 21
| 2,019
|
Image Deformation Meta-Networks for One-Shot Learning
| 206
|
cvpr
| 7
| 3
|
2023-06-03 02:17:50.161000
|
https://github.com/tankche1/IDeMe-Net
| 49
|
Image deformation meta-networks for one-shot learning
|
https://scholar.google.com/scholar?cluster=8511386292870768575&hl=en&as_sdt=0,1
| 3
| 2,019
|
GA-Net: Guided Aggregation Net for End-To-End Stereo Matching
| 554
|
cvpr
| 136
| 30
|
2023-06-03 02:17:50.361000
|
https://github.com/feihuzhang/GANet
| 507
|
Ga-net: Guided aggregation net for end-to-end stereo matching
|
https://scholar.google.com/scholar?cluster=731989336931762383&hl=en&as_sdt=0,49
| 26
| 2,019
|
Real-Time Self-Adaptive Deep Stereo
| 233
|
cvpr
| 73
| 19
|
2023-06-03 02:17:50.561000
|
https://github.com/CVLAB-Unibo/Real-time-self-adaptive-deep-stereo
| 405
|
Real-time self-adaptive deep stereo
|
https://scholar.google.com/scholar?cluster=18225618983635239070&hl=en&as_sdt=0,43
| 26
| 2,019
|
Occupancy Networks: Learning 3D Reconstruction in Function Space
| 1,770
|
cvpr
| 254
| 75
|
2023-06-03 02:17:50.761000
|
https://github.com/LMescheder/Occupancy-Networks
| 1,197
|
Occupancy networks: Learning 3d reconstruction in function space
|
https://scholar.google.com/scholar?cluster=14064961512731216993&hl=en&as_sdt=0,33
| 30
| 2,019
|
Detailed Human Shape Estimation From a Single Image by Hierarchical Mesh Deformation
| 120
|
cvpr
| 47
| 4
|
2023-06-03 02:17:50.961000
|
https://github.com/zhuhao-nju/hmd
| 265
|
Detailed human shape estimation from a single image by hierarchical mesh deformation
|
https://scholar.google.com/scholar?cluster=1439227329003947447&hl=en&as_sdt=0,33
| 15
| 2,019
|
Self-Calibrating Deep Photometric Stereo Networks
| 116
|
cvpr
| 29
| 0
|
2023-06-03 02:17:51.161000
|
https://github.com/guanyingc/SDPS-Net
| 155
|
Self-calibrating deep photometric stereo networks
|
https://scholar.google.com/scholar?cluster=3649234197372500195&hl=en&as_sdt=0,5
| 11
| 2,019
|
Argoverse: 3D Tracking and Forecasting With Rich Maps
| 865
|
cvpr
| 211
| 49
|
2023-06-03 02:17:51.361000
|
https://github.com/argoai/argoverse-api
| 720
|
Argoverse: 3d tracking and forecasting with rich maps
|
https://scholar.google.com/scholar?cluster=17363497644081299357&hl=en&as_sdt=0,44
| 28
| 2,019
|
Timeception for Complex Action Recognition
| 193
|
cvpr
| 35
| 5
|
2023-06-03 02:17:51.562000
|
https://github.com/noureldien/timeception
| 158
|
Timeception for complex action recognition
|
https://scholar.google.com/scholar?cluster=1175087663521850723&hl=en&as_sdt=0,11
| 8
| 2,019
|
Extreme Relative Pose Estimation for RGB-D Scans via Scene Completion
| 35
|
cvpr
| 17
| 1
|
2023-06-03 02:17:51.762000
|
https://github.com/zhenpeiyang/RelativePose
| 147
|
Extreme relative pose estimation for rgb-d scans via scene completion
|
https://scholar.google.com/scholar?cluster=9221764684170544668&hl=en&as_sdt=0,33
| 7
| 2,019
|
Long-Term Feature Banks for Detailed Video Understanding
| 436
|
cvpr
| 67
| 15
|
2023-06-03 02:17:51.962000
|
https://github.com/facebookresearch/video-long-term-feature-banks
| 364
|
Long-term feature banks for detailed video understanding
|
https://scholar.google.com/scholar?cluster=12076206268409002970&hl=en&as_sdt=0,48
| 11
| 2,019
|
IP102: A Large-Scale Benchmark Dataset for Insect Pest Recognition
| 199
|
cvpr
| 40
| 7
|
2023-06-03 02:17:52.162000
|
https://github.com/xpwu95/IP102
| 143
|
Ip102: A large-scale benchmark dataset for insect pest recognition
|
https://scholar.google.com/scholar?cluster=4487446333535453318&hl=en&as_sdt=0,44
| 9
| 2,019
|
What and How Well You Performed? A Multitask Learning Approach to Action Quality Assessment
| 84
|
cvpr
| 14
| 0
|
2023-06-03 02:17:52.362000
|
https://github.com/ParitoshParmar/MTL-AQA
| 42
|
What and how well you performed? a multitask learning approach to action quality assessment
|
https://scholar.google.com/scholar?cluster=16672989544412031563&hl=en&as_sdt=0,21
| 4
| 2,019
|
MHP-VOS: Multiple Hypotheses Propagation for Video Object Segmentation
| 46
|
cvpr
| 9
| 1
|
2023-06-03 02:17:52.563000
|
https://github.com/shuangjiexu/MHP-VOS
| 62
|
Mhp-vos: Multiple hypotheses propagation for video object segmentation
|
https://scholar.google.com/scholar?cluster=14226363239100634228&hl=en&as_sdt=0,33
| 6
| 2,019
|
SelFlow: Self-Supervised Learning of Optical Flow
| 305
|
cvpr
| 63
| 6
|
2023-06-03 02:17:52.762000
|
https://github.com/ppliuboy/SelFlow
| 387
|
Selflow: Self-supervised learning of optical flow
|
https://scholar.google.com/scholar?cluster=14077594709771456352&hl=en&as_sdt=0,21
| 14
| 2,019
|
UPSNet: A Unified Panoptic Segmentation Network
| 367
|
cvpr
| 118
| 76
|
2023-06-03 02:17:52.962000
|
https://github.com/uber-research/UPSNet
| 625
|
Upsnet: A unified panoptic segmentation network
|
https://scholar.google.com/scholar?cluster=18301475211197676940&hl=en&as_sdt=0,5
| 28
| 2,019
|
2.5D Visual Sound
| 163
|
cvpr
| 17
| 2
|
2023-06-03 02:17:53.162000
|
https://github.com/facebookresearch/FAIR-Play
| 84
|
2.5 d visual sound
|
https://scholar.google.com/scholar?cluster=15955658488872503923&hl=en&as_sdt=0,33
| 9
| 2,019
|
Taking a Deeper Look at the Inverse Compositional Algorithm
| 48
|
cvpr
| 29
| 2
|
2023-06-03 02:17:53.362000
|
https://github.com/lvzhaoyang/DeeperInverseCompositionalAlgorithm
| 152
|
Taking a deeper look at the inverse compositional algorithm
|
https://scholar.google.com/scholar?cluster=16780531933965862286&hl=en&as_sdt=0,5
| 15
| 2,019
|
JSIS3D: Joint Semantic-Instance Segmentation of 3D Point Clouds With Multi-Task Pointwise Networks and Multi-Value Conditional Random Fields
| 205
|
cvpr
| 34
| 2
|
2023-06-03 02:17:53.562000
|
https://github.com/pqhieu/JSIS3D
| 168
|
Jsis3d: Joint semantic-instance segmentation of 3d point clouds with multi-task pointwise networks and multi-value conditional random fields
|
https://scholar.google.com/scholar?cluster=16927809821668290492&hl=en&as_sdt=0,5
| 7
| 2,019
|
Deeper and Wider Siamese Networks for Real-Time Visual Tracking
| 820
|
cvpr
| 178
| 19
|
2023-06-03 02:17:53.761000
|
https://github.com/researchmm/SiamDW
| 737
|
Deeper and wider siamese networks for real-time visual tracking
|
https://scholar.google.com/scholar?cluster=17696051770837517858&hl=en&as_sdt=0,33
| 24
| 2,019
|
Instance Segmentation by Jointly Optimizing Spatial Embeddings and Clustering Bandwidth
| 248
|
cvpr
| 31
| 8
|
2023-06-03 02:17:53.961000
|
https://github.com/davyneven/SpatialEmbeddings
| 209
|
Instance segmentation by jointly optimizing spatial embeddings and clustering bandwidth
|
https://scholar.google.com/scholar?cluster=14151595211459682440&hl=en&as_sdt=0,5
| 15
| 2,019
|
Parsing R-CNN for Instance-Level Human Analysis
| 103
|
cvpr
| 36
| 25
|
2023-06-03 02:17:54.160000
|
https://github.com/soeaver/Parsing-R-CNN
| 283
|
Parsing r-cnn for instance-level human analysis
|
https://scholar.google.com/scholar?cluster=5570486802749692020&hl=en&as_sdt=0,33
| 24
| 2,019
|
Semantic Correlation Promoted Shape-Variant Context for Segmentation
| 164
|
cvpr
| 0
| 0
|
2023-06-03 02:17:54.360000
|
https://github.com/henghuiding/SVC
| 0
|
Semantic correlation promoted shape-variant context for segmentation
|
https://scholar.google.com/scholar?cluster=16130229518023869149&hl=en&as_sdt=0,33
| 0
| 2,019
|
Perceive Where to Focus: Learning Visibility-Aware Part-Level Features for Partial Person Re-Identification
| 311
|
cvpr
| 4
| 1
|
2023-06-03 02:17:54.561000
|
https://github.com/YifanSun-ReID/VPM-reID
| 28
|
Perceive where to focus: Learning visibility-aware part-level features for partial person re-identification
|
https://scholar.google.com/scholar?cluster=4047481609137728387&hl=en&as_sdt=0,33
| 1
| 2,019
|
Relation-Shape Convolutional Neural Network for Point Cloud Analysis
| 727
|
cvpr
| 74
| 20
|
2023-06-03 02:17:54.760000
|
https://github.com/Yochengliu/Relation-Shape-CNN
| 402
|
Relation-shape convolutional neural network for point cloud analysis
|
https://scholar.google.com/scholar?cluster=11483419455001652603&hl=en&as_sdt=0,1
| 21
| 2,019
|
Meta-Transfer Learning for Few-Shot Learning
| 976
|
cvpr
| 140
| 38
|
2023-06-03 02:17:54.960000
|
https://github.com/yaoyao-liu/meta-transfer-learning
| 661
|
Meta-transfer learning for few-shot learning
|
https://scholar.google.com/scholar?cluster=16670100435832438519&hl=en&as_sdt=0,33
| 24
| 2,019
|
ATOM: Accurate Tracking by Overlap Maximization
| 971
|
cvpr
| 577
| 55
|
2023-06-03 02:17:55.160000
|
https://github.com/visionml/pytracking
| 2,782
|
Atom: Accurate tracking by overlap maximization
|
https://scholar.google.com/scholar?cluster=963225988420087018&hl=en&as_sdt=0,5
| 90
| 2,019
|
Visual Tracking via Adaptive Spatially-Regularized Correlation Filters
| 366
|
cvpr
| 23
| 9
|
2023-06-03 02:17:55.361000
|
https://github.com/Daikenan/ASRCF
| 99
|
Visual tracking via adaptive spatially-regularized correlation filters
|
https://scholar.google.com/scholar?cluster=1936083344177917118&hl=en&as_sdt=0,5
| 7
| 2,019
|
BubbleNets: Learning to Select the Guidance Frame in Video Object Segmentation by Deep Sorting Frames
| 40
|
cvpr
| 19
| 5
|
2023-06-03 02:17:55.560000
|
https://github.com/griffbr/BubbleNets
| 100
|
Bubblenets: Learning to select the guidance frame in video object segmentation by deep sorting frames
|
https://scholar.google.com/scholar?cluster=1778787356825965594&hl=en&as_sdt=0,26
| 7
| 2,019
|
Deep RNN Framework for Visual Sequential Applications
| 41
|
cvpr
| 13
| 0
|
2023-06-03 02:17:55.760000
|
https://github.com/BoPang1996/Deep-RNN-Framework
| 45
|
Deep rnn framework for visual sequential applications
|
https://scholar.google.com/scholar?cluster=13952108559320750928&hl=en&as_sdt=0,1
| 6
| 2,019
|
Deep Tree Learning for Zero-Shot Face Anti-Spoofing
| 207
|
cvpr
| 54
| 19
|
2023-06-03 02:17:55.961000
|
https://github.com/yaojieliu/CVPR2019-DeepTreeLearningForZeroShotFaceAntispoofing
| 180
|
Deep tree learning for zero-shot face anti-spoofing
|
https://scholar.google.com/scholar?cluster=4809478454905690384&hl=en&as_sdt=0,32
| 13
| 2,019
|
Collaborative Global-Local Networks for Memory-Efficient Segmentation of Ultra-High Resolution Images
| 104
|
cvpr
| 78
| 7
|
2023-06-03 02:17:56.161000
|
https://github.com/chenwydj/ultra_high_resolution_segmentation
| 312
|
Collaborative global-local networks for memory-efficient segmentation of ultra-high resolution images
|
https://scholar.google.com/scholar?cluster=9353770986207663680&hl=en&as_sdt=0,25
| 12
| 2,019
|
Graph-Based Global Reasoning Networks
| 416
|
cvpr
| 48
| 8
|
2023-06-03 02:17:56.361000
|
https://github.com/facebookresearch/GloRe
| 193
|
Graph-based global reasoning networks
|
https://scholar.google.com/scholar?cluster=7036510083148234312&hl=en&as_sdt=0,5
| 9
| 2,019
|
ArcFace: Additive Angular Margin Loss for Deep Face Recognition
| 4,654
|
cvpr
| 4,361
| 952
|
2023-06-03 02:17:56.561000
|
https://github.com/deepinsight/insightface
| 15,442
|
Arcface: Additive angular margin loss for deep face recognition
|
https://scholar.google.com/scholar?cluster=14066082468781799933&hl=en&as_sdt=0,21
| 476
| 2,019
|
Efficient Parameter-Free Clustering Using First Neighbor Relations
| 133
|
cvpr
| 53
| 0
|
2023-06-03 02:17:56.761000
|
https://github.com/ssarfraz/FINCH-CLustering
| 277
|
Efficient parameter-free clustering using first neighbor relations
|
https://scholar.google.com/scholar?cluster=5006622334338007650&hl=en&as_sdt=0,5
| 22
| 2,019
|
Reversible GANs for Memory-Efficient Image-To-Image Translation
| 41
|
cvpr
| 10
| 10
|
2023-06-03 02:17:56.962000
|
https://github.com/tychovdo/RevGAN
| 79
|
Reversible gans for memory-efficient image-to-image translation
|
https://scholar.google.com/scholar?cluster=15019867665042081663&hl=en&as_sdt=0,33
| 10
| 2,019
|
Latent Space Autoregression for Novelty Detection
| 386
|
cvpr
| 60
| 9
|
2023-06-03 02:17:57.162000
|
https://github.com/aimagelab/novelty-detection
| 185
|
Latent space autoregression for novelty detection
|
https://scholar.google.com/scholar?cluster=18196632214960310707&hl=en&as_sdt=0,14
| 11
| 2,019
|
Feature Denoising for Improving Adversarial Robustness
| 784
|
cvpr
| 86
| 2
|
2023-06-03 02:17:57.362000
|
https://github.com/facebookresearch/ImageNet-Adversarial-Training
| 664
|
Feature denoising for improving adversarial robustness
|
https://scholar.google.com/scholar?cluster=961363392550158116&hl=en&as_sdt=0,39
| 20
| 2,019
|
Selective Kernel Networks
| 1,592
|
cvpr
| 105
| 6
|
2023-06-03 02:17:57.562000
|
https://github.com/implus/SKNet
| 542
|
Selective kernel networks
|
https://scholar.google.com/scholar?cluster=11785614849903023316&hl=en&as_sdt=0,5
| 9
| 2,019
|
FlowNet3D: Learning Scene Flow in 3D Point Clouds
| 354
|
cvpr
| 84
| 18
|
2023-06-03 02:17:57.762000
|
https://github.com/xingyul/flownet3d
| 339
|
Flownet3d: Learning scene flow in 3d point clouds
|
https://scholar.google.com/scholar?cluster=15188873080391320732&hl=en&as_sdt=0,47
| 13
| 2,019
|
Bag of Tricks for Image Classification with Convolutional Neural Networks
| 1,246
|
cvpr
| 1,198
| 60
|
2023-06-03 02:17:57.961000
|
https://github.com/dmlc/gluon-cv
| 5,561
|
Bag of tricks for image classification with convolutional neural networks
|
https://scholar.google.com/scholar?cluster=8341554460743296519&hl=en&as_sdt=0,33
| 154
| 2,019
|
Parametric Noise Injection: Trainable Randomness to Improve Deep Neural Network Robustness Against Adversarial Attack
| 228
|
cvpr
| 16
| 2
|
2023-06-03 02:17:58.163000
|
https://github.com/elliothe/CVPR_2019_PNI
| 38
|
Parametric noise injection: Trainable randomness to improve deep neural network robustness against adversarial attack
|
https://scholar.google.com/scholar?cluster=3553606349914507364&hl=en&as_sdt=0,6
| 2
| 2,019
|
Strike (With) a Pose: Neural Networks Are Easily Fooled by Strange Poses of Familiar Objects
| 276
|
cvpr
| 16
| 0
|
2023-06-03 02:17:58.362000
|
https://github.com/airalcorn2/strike-with-a-pose
| 75
|
Strike (with) a pose: Neural networks are easily fooled by strange poses of familiar objects
|
https://scholar.google.com/scholar?cluster=16755141960750698067&hl=en&as_sdt=0,11
| 5
| 2,019
|
SparseFool: A Few Pixels Make a Big Difference
| 152
|
cvpr
| 11
| 0
|
2023-06-03 02:17:58.562000
|
https://github.com/LTS4/SparseFool
| 48
|
Sparsefool: a few pixels make a big difference
|
https://scholar.google.com/scholar?cluster=6158227118856345030&hl=en&as_sdt=0,44
| 4
| 2,019
|
Invariance Matters: Exemplar Memory for Domain Adaptive Person Re-Identification
| 572
|
cvpr
| 61
| 8
|
2023-06-03 02:17:58.762000
|
https://github.com/zhunzhong07/ECN
| 297
|
Invariance matters: Exemplar memory for domain adaptive person re-identification
|
https://scholar.google.com/scholar?cluster=1740171451548448125&hl=en&as_sdt=0,5
| 11
| 2,019
|
Dissecting Person Re-Identification From the Viewpoint of Viewpoint
| 180
|
cvpr
| 15
| 1
|
2023-06-03 02:17:58.971000
|
https://github.com/sxzrt/Dissecting-Person-Re-ID-from-the-Viewpoint-of-Viewpoint
| 117
|
Dissecting person re-identification from the viewpoint of viewpoint
|
https://scholar.google.com/scholar?cluster=6413659946848887161&hl=en&as_sdt=0,1
| 8
| 2,019
|
Instance-Level Meta Normalization
| 25
|
cvpr
| 3
| 0
|
2023-06-03 02:17:59.173000
|
https://github.com/Gasoonjia/ILM-Norm
| 17
|
Instance-level meta normalization
|
https://scholar.google.com/scholar?cluster=17437121449575767985&hl=en&as_sdt=0,5
| 2
| 2,019
|
Iterative Normalization: Beyond Standardization Towards Efficient Whitening
| 93
|
cvpr
| 4
| 0
|
2023-06-03 02:17:59.373000
|
https://github.com/huangleiBuaa/IterNorm
| 22
|
Iterative normalization: Beyond standardization towards efficient whitening
|
https://scholar.google.com/scholar?cluster=17943009712133460569&hl=en&as_sdt=0,5
| 4
| 2,019
|
Fast Neural Architecture Search of Compact Semantic Segmentation Models via Auxiliary Cells
| 150
|
cvpr
| 25
| 2
|
2023-06-03 02:17:59.574000
|
https://github.com/drsleep/nas-segm-pytorch
| 143
|
Fast neural architecture search of compact semantic segmentation models via auxiliary cells
|
https://scholar.google.com/scholar?cluster=8910584954060361446&hl=en&as_sdt=0,5
| 8
| 2,019
|
Generating 3D Adversarial Point Clouds
| 214
|
cvpr
| 26
| 3
|
2023-06-03 02:17:59.774000
|
https://github.com/xiangchong1/3d-adv-pc
| 92
|
Generating 3d adversarial point clouds
|
https://scholar.google.com/scholar?cluster=10039699469817980264&hl=en&as_sdt=0,5
| 6
| 2,019
|
Partial Order Pruning: For Best Speed/Accuracy Trade-Off in Neural Architecture Search
| 128
|
cvpr
| 25
| 1
|
2023-06-03 02:17:59.974000
|
https://github.com/lixincn2015/Partial-Order-Pruning
| 147
|
Partial order pruning: for best speed/accuracy trade-off in neural architecture search
|
https://scholar.google.com/scholar?cluster=8555049247914418659&hl=en&as_sdt=0,5
| 6
| 2,019
|
Memory in Memory: A Predictive Neural Network for Learning Higher-Order Non-Stationarity From Spatiotemporal Dynamics
| 204
|
cvpr
| 38
| 7
|
2023-06-03 02:18:00.175000
|
https://github.com/Yunbo426/MIM
| 137
|
Memory in memory: A predictive neural network for learning higher-order non-stationarity from spatiotemporal dynamics
|
https://scholar.google.com/scholar?cluster=15070346920682817473&hl=en&as_sdt=0,5
| 5
| 2,019
|
Distilling Object Detectors With Fine-Grained Feature Imitation
| 264
|
cvpr
| 70
| 22
|
2023-06-03 02:18:00.375000
|
https://github.com/twangnh/Distilling-Object-Detectors
| 402
|
Distilling object detectors with fine-grained feature imitation
|
https://scholar.google.com/scholar?cluster=5085359464416711778&hl=en&as_sdt=0,11
| 10
| 2,019
|
Adapting Object Detectors via Selective Cross-Domain Alignment
| 294
|
cvpr
| 15
| 4
|
2023-06-03 02:18:00.576000
|
https://github.com/xinge008/SCDA
| 78
|
Adapting object detectors via selective cross-domain alignment
|
https://scholar.google.com/scholar?cluster=7497629776340245603&hl=en&as_sdt=0,20
| 2
| 2,019
|
Centripetal SGD for Pruning Very Deep Convolutional Networks With Complicated Structure
| 162
|
cvpr
| 12
| 2
|
2023-06-03 02:18:00.775000
|
https://github.com/ShawnDing1994/Centripetal-SGD
| 59
|
Centripetal sgd for pruning very deep convolutional networks with complicated structure
|
https://scholar.google.com/scholar?cluster=17050571465031021795&hl=en&as_sdt=0,5
| 5
| 2,019
|
Cyclic Guidance for Weakly Supervised Joint Detection and Segmentation
| 110
|
cvpr
| 5
| 2
|
2023-06-03 02:18:00.976000
|
https://github.com/shenyunhang/WS-JDS
| 19
|
Cyclic guidance for weakly supervised joint detection and segmentation
|
https://scholar.google.com/scholar?cluster=764160567722431856&hl=en&as_sdt=0,5
| 1
| 2,019
|
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