整理：AI算法与图像处理，分享请注明出处
CVPR2022论文和代码整理：https://github.com/DWCTOD/CVPR2022-Papers-with-Code-Demo
欢迎关注：
A Simple Multi-Modality Transfer Learning Baseline for Sign Language Translation
- 论文/Paper：https://arxiv.org/abs/2203.04287
- 代码/Code：
Probabilistic Warp Consistency for Weakly-Supervised Semantic Correspondences
- 论文/Paper：https://arxiv.org/abs/2203.04279
- 代码/Code：https://github.com/PruneTruong/DenseMatching
End-to-End Semi-Supervised Learning for Video Action Detection
- 论文/Paper：https://arxiv.org/abs/2203.04251
- 代码/Code：
Neural Face Identification in a 2D Wireframe Projection of a Manifold Object
- 论文/Paper：https://arxiv.org/abs/2203.04229
- 代码/Code：https://github.com/manycore-research/faceformer
- 主页：https://manycore-research.github.io/faceformer/
Selective-Supervised Contrastive Learning with Noisy Labels
- 论文/Paper：https://arxiv.org/abs/2203.04181
- 代码/Code：https://github.com/ShikunLi/Sel-CL
Motron: Multimodal Probabilistic Human Motion Forecasting
- 论文/Paper：https://arxiv.org/abs/2203.04132
- 代码/Code：
E2EC: An End-to-End Contour-based Method for High-Quality High-Speed Instance Segmentation
- 论文/Paper：https://arxiv.org/abs/2203.04074
- 代码/Code：https://github.com/zhang-tao-whu/e2ec
Shape-invariant 3D Adversarial Point Clouds
- 论文/Paper：https://arxiv.org/abs/2203.04041
- 代码/Code：https://github.com/shikiw/SI-Adv
DeltaCNN: End-to-End CNN Inference of Sparse Frame Differences in Videos
- 论文/Paper：https://arxiv.org/abs/2203.03996
- 代码/Code：
Generative Cooperative Learning for Unsupervised Video Anomaly Detection
- 论文/Paper：https://arxiv.org/abs/2203.03962
- 代码/Code：
ART-Point: Improving Rotation Robustness of Point Cloud Classifiers via Adversarial Rotation
- 论文/Paper：https://arxiv.org/abs/2203.03888
- 代码/Code：
Semi-Supervised Semantic Segmentation Using Unreliable Pseudo-Labels
- 论文/Paper：https://arxiv.org/abs/2203.03884
- 代码/Code：
Weakly Supervised Semantic Segmentation using Out-of-Distribution Data
- 论文/Paper：https://arxiv.org/abs/2203.03860
- 代码/Code：
Deep Rectangling for Image Stitching: A Learning Baseline
- 论文/Paper：https://arxiv.org/abs/2203.03831
- 代码/Code：https://github.com/nie-lang/DeepRectangling
Shadows can be Dangerous: Stealthy and Effective Physical-world Adversarial Attack by Natural Phenomenon
- 论文/Paper：https://arxiv.org/abs/2203.03818
- 代码/Code：
Unknown-Aware Object Detection: Learning What You Don't Know from Videos in the Wild
- 论文/Paper：https://arxiv.org/abs/2203.03800
- 代码/Code：https://github.com/deeplearning-wisc/stud
On Generalizing Beyond Domains in Cross-Domain Continual Learning
- 论文/Paper：https://arxiv.org/abs/2203.03970
- 代码/Code：
Generating 3D Bio-Printable Patches Using Wound Segmentation and Reconstruction to Treat Diabetic Foot Ulcers
- 论文/Paper：https://arxiv.org/abs/2203.03814
- 代码/Code：
