CVPR2021 | CVPR2021最全整理,CVPR2021下载链接,CVPR2021全部论文代码
CVPR2021年的官网:
CVPR2021最全1660篇pdf(4.3G)
链接: https://pan.baidu.com/s/1GWkqUOcO6KMOu-uLJrSpbA 提取码: vwkx
我自己总结持续更新Github上面:https://github.com/Sophia-11/Awesome-CVPR-Paper
2021持续论文集锦百度云请在【计算机视觉联盟】后台回复 CVPR2021
往年论文集锦请在【计算机视觉联盟】后台回复 CVPR2019
2020持续论文集锦请在【计算机视觉联盟】后台回复 CVPR2020
CVPR2021最新更新论文
Image-to-image Translation via Hierarchical Style Disentanglement Xinyang Li, Shengchuan Zhang, Jie Hu, Liujuan Cao, Xiaopeng Hong, Xudong Mao, Feiyue Huang, Yongjian Wu, Rongrong Ji https://arxiv.org/abs/2103.01456 https://github.com/imlixinyang/HiSD
FLAVR: Flow-Agnostic Video Representations for Fast Frame Interpolation https://arxiv.org/pdf/2012.08512.pdf https://tarun005.github.io/FLAVR/Code https://tarun005.github.io/FLAVR/
Patch-NetVLAD: Multi-Scale Fusion of Locally-Global Descriptors for Place Recognition Stephen Hausler, Sourav Garg, Ming Xu, Michael Milford, Tobias Fischer https://arxiv.org/abs/2103.01486
Depth from Camera Motion and Object Detection Brent A. Griffin, Jason J. Corso https://arxiv.org/abs/2103.01468
UP-DETR: Unsupervised Pre-training for Object Detection with Transformers https://arxiv.org/pdf/2011.09094.pdf
Multi-Stage Progressive Image Restoration https://arxiv.org/abs/2102.02808 https://github.com/swz30/MPRNet
Weakly Supervised Learning of Rigid 3D Scene Flow https://arxiv.org/pdf/2102.08945.pdf https://arxiv.org/pdf/2102.08945.pdf https://3dsceneflow.github.io/
Exploring Complementary Strengths of Invariant and Equivariant Representations for Few-Shot Learning Mamshad Nayeem Rizve, Salman Khan, Fahad Shahbaz Khan, Mubarak Shah https://arxiv.org/abs/2103.01315
Re-labeling ImageNet: from Single to Multi-Labels, from Global to Localized Labels https://arxiv.org/abs/2101.05022 https://github.com/naver-ai/relabel_imagenet
Rethinking Channel Dimensions for Efficient Model Design https://arxiv.org/abs/2007.00992 https://github.com/clovaai/rexnet
Coarse-Fine Networks for Temporal Activity Detection in Videos Kumara Kahatapitiya, Michael S. Ryoo https://arxiv.org/abs/2103.01302
A Deep Emulator for Secondary Motion of 3D Characters Mianlun Zheng, Yi Zhou, Duygu Ceylan, Jernej Barbic https://arxiv.org/abs/2103.01261
Fair Attribute Classification through Latent Space De-biasing https://arxiv.org/abs/2012.01469 https://github.com/princetonvisualai/gan-debiasing https://princetonvisualai.github.io/gan-debiasing/
Auto-Exposure Fusion for Single-Image Shadow Removal Lan Fu, Changqing Zhou, Qing Guo, Felix Juefei-Xu, Hongkai Yu, Wei Feng, Yang Liu, Song Wang https://arxiv.org/abs/2103.01255
Less is More: CLIPBERT for Video-and-Language Learning via Sparse Sampling https://arxiv.org/pdf/2102.06183.pdf https://github.com/jayleicn/ClipBERT
MetaSCI: Scalable and Adaptive Reconstruction for Video Compressive Sensing Zhengjue Wang, Hao Zhang, Ziheng Cheng, Bo Chen, Xin Yuan https://arxiv.org/abs/2103.01786
AttentiveNAS: Improving Neural Architecture Search via Attentive https://arxiv.org/pdf/2011.09011.pdf
Diffusion Probabilistic Models for 3D Point Cloud Generation Shitong Luo, Wei Hu https://arxiv.org/abs/2103.01458
There is More than Meets the Eye: Self-Supervised Multi-Object Detection and Tracking with Sound by Distilling Multimodal Knowledge Francisco Rivera Valverde, Juana Valeria Hurtado, Abhinav Valada https://arxiv.org/abs/2103.01353 http://rl.uni-freiburg.de/research/multimodal-distill
Encoding in Style: a StyleGAN Encoder for Image-to-Image Translation https://arxiv.org/abs/2008.00951 https://github.com/eladrich/pixel2style2pixel https://eladrich.github.io/pixel2style2pixel/
Hierarchical and Partially Observable Goal-driven Policy Learning with Goals Relational Graph Xin Ye, Yezhou Yang https://arxiv.org/abs/2103.01350
RepVGG: Making VGG-style ConvNets Great Again https://arxiv.org/abs/2101.03697 https://github.com/megvii-model/RepVGG
Transformer Interpretability Beyond Attention Visualization https://arxiv.org/pdf/2012.09838.pdf https://github.com/hila-chefer/Transformer-Explainability
PREDATOR: Registration of 3D Point Clouds with Low Overlap https://arxiv.org/pdf/2011.13005.pdf https://github.com/ShengyuH/OverlapPredator https://overlappredator.github.io/
往年2020年论文回归
目标检测
Bridging the Gap Between Anchor-based and Anchor-free Detection via Adaptive Training Sample Selection 论文地址:https://arxiv.org/abs/1912.02424
代码:https://github.com/sfzhang15/ATSSFew-Shot Object Detection with Attention-RPN and Multi-Relation Detector 论文地址:https://arxiv.org/abs/1908.01998
图像分割
Semi-Supervised Semantic Image Segmentation with Self-correcting Networks 论文地址:https://arxiv.org/abs/1811.07073
Deep Snake for Real-Time Instance Segmentation 论文地址:https://arxiv.org/abs/2001.01629
CenterMask : Real-Time Anchor-Free Instance Segmentation 论文地址:https://arxiv.org/abs/1911.06667 代码:https://github.com/youngwanLEE/CenterMask
SketchGCN: Semantic Sketch Segmentation with Graph Convolutional Networks 论文地址:https://arxiv.org/abs/2003.00678
PolarMask: Single Shot Instance Segmentation with Polar Representation 论文地址:https://arxiv.org/abs/1909.13226 代码:https://github.com/xieenze/PolarMask
xMUDA: Cross-Modal Unsupervised Domain Adaptation for 3D Semantic Segmentation 论文地址:https://arxiv.org/abs/1911.12676
BlendMask: Top-Down Meets Bottom-Up for Instance Segmentation 论文地址:https://arxiv.org/abs/2001.00309
人脸识别
Towards Universal Representation Learning for Deep Face Recognition 论文地址:https://arxiv.org/abs/2002.11841
Suppressing Uncertainties for Large-Scale Facial Expression Recognition
论文地址:https://arxiv.org/abs/2002.10392 代码:https://github.com/kaiwang960112/Self-Cure-Network
3.Face X-ray for More General Face Forgery Detection 论文地址:https://arxiv.org/pdf/1912.13458.pdf
目标跟踪
1.ROAM: Recurrently Optimizing Tracking Model 论文地址:https://arxiv.org/abs/1907.12006
三维点云&重建
PF-Net: Point Fractal Network for 3D Point Cloud Completion 论文地址:https://arxiv.org/abs/2003.00410
PointAugment: an Auto-Augmentation Framework for Point Cloud Classification 论文地址:https://arxiv.org/abs/2002.10876 代码:https://github.com/liruihui/PointAugment/
3.Learning multiview 3D point cloud registration 论文地址:https://arxiv.org/abs/2001.05119
C-Flow: Conditional Generative Flow Models for Images and 3D Point Clouds 论文地址:https://arxiv.org/abs/1912.07009
RandLA-Net: Efficient Semantic Segmentation of Large-Scale Point Clouds 论文地址:https://arxiv.org/abs/1911.11236
Total3DUnderstanding: Joint Layout, Object Pose and Mesh Reconstruction for Indoor Scenes from a Single Image 论文地址:https://arxiv.org/abs/2002.12212
Implicit Functions in Feature Space for 3D Shape Reconstruction and Completion 论文地址:https://arxiv.org/abs/2003.01456
In Perfect Shape: Certifiably Optimal 3D Shape Reconstruction from 2D Landmarks 论文地址:https://arxiv.org/pdf/1911.11924.pdf
姿态估计
VIBE: Video Inference for Human Body Pose and Shape Estimation 论文地址:https://arxiv.org/abs/1912.05656
代码:https://github.com/mkocabas/VIBEDistribution-Aware Coordinate Representation for Human Pose Estimation 论文地址:https://arxiv.org/abs/1910.06278
代码:https://github.com/ilovepose/DarkPose4D Association Graph for Realtime Multi-person Motion Capture Using Multiple Video Cameras 论文地址:https://arxiv.org/abs/2002.12625
Optimal least-squares solution to the hand-eye calibration problem 论文地址:https://arxiv.org/abs/2002.10838
D3VO: Deep Depth, Deep Pose and Deep Uncertainty for Monocular Visual Odometry 论文地址:https://arxiv.org/abs/2003.01060
Multi-Modal Domain Adaptation for Fine-Grained Action Recognition 论文地址:https://arxiv.org/abs/2001.09691
Distribution Aware Coordinate Representation for Human Pose Estimation 论文地址:https://arxiv.org/abs/1910.06278
The Devil is in the Details: Delving into Unbiased Data Processing for Human Pose Estimation 论文地址:https://arxiv.org/abs/1911.07524
9.PVN3D: A Deep Point-wise 3D Keypoints Voting Network for 6DoF Pose Estimation 论文地址:https://arxiv.org/abs/1911.04231
GAN
Your Local GAN: Designing Two Dimensional Local Attention Mechanisms for Generative Models 论文地址:https://arxiv.org/abs/1911.12287 代码:https://github.com/giannisdaras/ylg
MSG-GAN: Multi-Scale Gradient GAN for Stable Image Synthesis 论文地址:https://arxiv.org/abs/1903.06048
Robust Design of Deep Neural Networks against Adversarial Attacks based on Lyapunov Theory 论文地址:https://arxiv.org/abs/1911.04636
小样本&零样本
- Improved Few-Shot Visual Classification 论文地址:https://arxiv.org/pdf/1912.03432.pdf
2.Meta-Transfer Learning for Zero-Shot Super-Resolution 论文地址:https://arxiv.org/abs/2002.12213
弱监督&无监督
- Rethinking the Route Towards Weakly Supervised Object Localization 论文地址:https://arxiv.org/abs/2002.11359
- NestedVAE: Isolating Common Factors via Weak Supervision 论文地址:https://arxiv.org/abs/2002.11576
3.Unsupervised Reinforcement Learning of Transferable Meta-Skills for Embodied Navigation 论文地址:https://arxiv.org/abs/1911.07450
4.Disentangling Physical Dynamics from Unknown Factors for Unsupervised Video Prediction 论文地址:https://arxiv.org/abs/2003.01460
神经网络
Visual Commonsense R-CNN 论文地址:https://arxiv.org/abs/2002.12204
GhostNet: More Features from Cheap Operations 论文地址:https://arxiv.org/abs/1911.11907 代码:https://github.com/iamhankai/ghostnet
Watch your Up-Convolution: CNN Based Generative Deep Neural Networks are Failing to Reproduce Spectral 论文地址:https://arxiv.org/abs/2003.01826
模型加速
- GPU-Accelerated Mobile Multi-view Style Transfer 论文地址:https://arxiv.org/abs/2003.00706
视觉常识
- What it Thinks is Important is Important: Robustness Transfers through Input Gradients 论文地址:https://arxiv.org/abs/1912.05699
2.Attentive Context Normalization for Robust Permutation-Equivariant Learning 论文地址:https://arxiv.org/abs/1907.02545
Bundle Adjustment on a Graph Processor 论文地址:https://arxiv.org/abs/2003.03134 https://github.com/joeaortiz/gbp
Transferring Dense Pose to Proximal Animal Classes 论文地址:https://arxiv.org/abs/2003.00080
Representations, Metrics and Statistics For Shape Analysis of Elastic Graphs 论文地址:https://arxiv.org/abs/2003.00287
Learning in the Frequency Domain 论文地址:https://arxiv.org/abs/2002.12416
7.Filter Grafting for Deep Neural Networks 论文地址:https://arxiv.org/pdf/2001.05868.pdf
8.ClusterFit: Improving Generalization of Visual Representations 论文地址:https://arxiv.org/abs/1912.03330
9.Social-STGCNN: A Social Spatio-Temporal Graph Convolutional Neural Network for Human Trajectory Prediction 论文地址:https://arxiv.org/abs/2002.11927
10.Auto-Encoding Twin-Bottleneck Hashing 论文地址:https://arxiv.org/abs/2002.11930
11.Learning Representations by Predicting Bags of Visual Words 论文地址:https://arxiv.org/abs/2002.12247
12.Holistically-Attracted Wireframe Parsing 论文地址:https://arxiv.org/abs/2003.01663
13.A General and Adaptive Robust Loss Function 论文地址:https://arxiv.org/abs/1701.03077
14.A Characteristic Function Approach to Deep Implicit Generative Modeling 论文地址:https://arxiv.org/abs/1909.07425
15.AdderNet: Do We Really Need Multiplications in Deep Learning? 论文地址:https://arxiv.org/pdf/1912.13200
16.12-in-1: Multi-Task Vision and Language Representation Learning 论文地址:https://arxiv.org/abs/1912.02315
17.Making Better Mistakes: Leveraging Class Hierarchies with Deep Networks 论文地址:https://arxiv.org/abs/1912.09393
18.CARS: Contunuous Evolution for Efficient Neural Architecture Search 论文地址:https://arxiv.org/pdf/1909.04977.pdf 代码:https://github.com/huawei-noah/CARS
19.Towards Learning a Generic Agent for Vision-and-Language Navigation via Pre-training 论文地址:https://arxiv.org/abs/2002.10638 代码:https://github.com/weituo12321/PREVALENT
1.GhostNet: More Features from Cheap Operations(超越Mobilenet v3的架构) 论文链接:https://arxiv.org/pdf/1911.11907arxiv.org 模型(在ARM CPU上的表现惊人):https://github.com/iamhankai/ghostnetgithub.com
We beat other SOTA lightweight CNNs such as MobileNetV3 and FBNet.
AdderNet: Do We Really Need Multiplications in Deep Learning? (加法神经网络) 在大规模神经网络和数据集上取得了非常好的表现 论文链接:https://arxiv.org/pdf/1912.13200arxiv.org
Frequency Domain Compact 3D Convolutional Neural Networks (3dCNN压缩) 论文链接:https://arxiv.org/pdf/1909.04977arxiv.org 开源代码:https://github.com/huawei-noah/CARSgithub.com
A Semi-Supervised Assessor of Neural Architectures (神经网络精度预测器 NAS)
Hit-Detector: Hierarchical Trinity Architecture Search for Object Detection (NAS 检测) backbone-neck-head一起搜索, 三位一体
CARS: Contunuous Evolution for Efficient Neural Architecture Search (连续进化的NAS) 高效,具备可微和进化的多重优势,且能输出帕累托前研
On Positive-Unlabeled Classification in GAN (PU+GAN)
Learning multiview 3D point cloud registration(3D点云) 论文链接:arxiv.org/abs/2001.05119
Multi-Modal Domain Adaptation for Fine-Grained Action Recognition(细粒度动作识别) 论文链接:arxiv.org/abs/2001.09691
Action Modifiers:Learning from Adverbs in Instructional Video 论文链接:arxiv.org/abs/1912.06617
PolarMask: Single Shot Instance Segmentation with Polar Representation(实例分割建模) 论文链接:arxiv.org/abs/1909.13226 论文解读:https://zhuanlan.zhihu.com/p/84890413 开源代码:https://github.com/xieenze/PolarMask
Rethinking Performance Estimation in Neural Architecture Search(NAS) 由于block wise neural architecture search中真正消耗时间的是performance estimation部分,本文针对 block wise的NAS找到了最优参数,速度更快,且相关度更高。
Distribution Aware Coordinate Representation for Human Pose Estimation(人体姿态估计) 论文链接:arxiv.org/abs/1910.06278 Github:https://github.com/ilovepose/DarkPose 作者团队主页:https://ilovepose.github.io/coco/
OCR
- ABCNet: Real-time Scene Text Spotting with Adaptive Bezier-Curve Network 论文地址:https://arxiv.org/abs/2002.10200 代码:https://github.com/Yuliang-Liu/bezier_curve_text_spotting,https://github.com/aim-uofa/adet
图像分类
Self-training with Noisy Student improves ImageNet classification 论文地址:https://arxiv.org/abs/1911.04252
Image Matching across Wide Baselines: From Paper to Practice 论文地址:https://arxiv.org/abs/2003.01587
Towards Robust Image Classification Using Sequential Attention Models 论文地址:https://arxiv.org/abs/1912.02184
视频分析
Rethinking Zero-shot Video Classification: End-to-end Training for Realistic Applications 论文地址:https://arxiv.org/abs/2003.01455
代码:https://github.com/bbrattoli/ZeroShotVideoClassificationSay As You Wish: Fine-grained Control of Image Caption Generation with Abstract Scene Graphs 论文地址:https://arxiv.org/abs/2003.00387
Fine-grained Video-Text Retrieval with Hierarchical Graph Reasoning 论文地址:https://arxiv.org/abs/2003.00392
Object Relational Graph with Teacher-Recommended Learning for Video Captioning 论文地址:https://arxiv.org/abs/2002.11566
Zooming Slow-Mo: Fast and Accurate One-Stage Space-Time Video Super-Resolution 论文地址:https://arxiv.org/abs/2002.11616
Blurry Video Frame Interpolation 论文地址:https://arxiv.org/abs/2002.12259
Hierarchical Conditional Relation Networks for Video Question Answering 论文地址:https://arxiv.org/abs/2002.10698
Action Modifiers:Learning from Adverbs in Instructional Video 论文地址:https://arxiv.org/abs/1912.06617
图像处理
- Learning to Shade Hand-drawn Sketches 论文地址:https://arxiv.org/abs/2002.11812
2.Single Image Reflection Removal through Cascaded Refinement 论文地址:https://arxiv.org/abs/1911.06634
3.Generalized ODIN: Detecting Out-of-distribution Image without Learning from Out-of-distribution Data 论文地址:https://arxiv.org/abs/2002.11297
Deep Image Harmonization via Domain Verification 论文地址:https://arxiv.org/abs/1911.13239 代码:https://github.com/bcmi/Image_Harmonization_Datasets
RoutedFusion: Learning Real-time Depth Map Fusion 论文地址:https://arxiv.org/pdf/2001.04388.pdf
更新
- 视觉常识R-CNN,Visual Commonsense R-CNN
https://arxiv.org/abs/2002.12204
- Out-of-distribution图像检测
https://arxiv.org/abs/2002.11297
- 模糊视频帧插值,Blurry Video Frame Interpolation
https://arxiv.org/abs/2002.12259
- 元迁移学习零样本超分
https://arxiv.org/abs/2002.12213
- 3D室内场景理解
https://arxiv.org/abs/2002.12212
6.从有偏训练生成无偏场景图
https://arxiv.org/abs/2002.11949
- 自动编码双瓶颈哈希
https://arxiv.org/abs/2002.11930
- 一种用于人类轨迹预测的社会时空图卷积神经网络
https://arxiv.org/abs/2002.11927
- 面向面向深度人脸识别的通用表示学习
https://arxiv.org/abs/2002.11841
- 视觉表示泛化性
https://arxiv.org/abs/1912.03330
- 减弱上下文偏差
https://arxiv.org/abs/2002.11812
- 可迁移元技能的无监督强化学习
https://arxiv.org/abs/1911.07450
- 快速准确时空视频超分
https://arxiv.org/abs/2002.11616
- 对象关系图Teacher推荐学习的视频captioning
https://arxiv.org/abs/2002.11566
- 弱监督物体定位路由再思考
https://arxiv.org/abs/2002.11359
- 通过预培训学习视觉和语言导航的通用代理
https://arxiv.org/pdf/2002.10638.pdf
- GhostNet轻量级神经网络
https://arxiv.org/pdf/1911.11907.pdf
- AdderNet:在深度学习中,我们真的需要乘法吗?
https://arxiv.org/pdf/1912.13200.pdf
- CARS:高效神经结构搜索的持续进化
https://arxiv.org/abs/1909.04977
- 通过协作式的迭代级联微调来移除单图像中的反射
https://arxiv.org/abs/1911.06634
- 深度神经网络的滤波嫁接
https://arxiv.org/pdf/2001.05868.pdf
- PolarMask:将实例分割统一到FCN
https://arxiv.org/pdf/1909.13226.pdf
- 半监督语义图像分割
https://arxiv.org/pdf/1811.07073.pdf
- 通过选择性的特征再生来抵御通用攻击
https://arxiv.org/pdf/1906.03444.pdf
- 实时的基于细粒度草图的图像检索
https://arxiv.org/abs/2002.10310
- 用子问题询问VQA模型
https://arxiv.org/abs/1906.03444
- 从2D范例中学习神经三维纹理空间
https://geometry.cs.ucl.ac.uk/projects/2020/neuraltexture/
- NestedVAE:通过薄弱的监督来隔离共同因素
https://arxiv.org/abs/2002.11576
- 实现多未来轨迹预测
https://arxiv.org/pdf/1912.06445.pdf
- 使用序列注意力模型进行稳健的图像分类
https://arxiv.org/pdf/1912.02184
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