本文整理来自Twitter、arXiv、知乎放出来的15篇最新ICCV Oral论文,方便大家抢先阅览!
最近计算机视觉三大顶会之一ICCV2021接收结果已经公布,本次ICCV共计 6236 篇有效提交论文,其中有 1617 篇论文被接收,接收率为25.9%。小编在这里整理来自Twitter、arXiv、知乎放出来的15篇最新ICCV Oral论文,方便大家抢先阅览!这些论文包括目标检测、域自适应、因果推理、语义分割等。1. BARF:束调整神经辐射场,BARF: Bundle-Adjusting Neural Radiance Fields
https://chenhsuanlin.bitbucket.io/bundle-adjusting-NeRF/
2. 端到端多模态理解的调制检测,MDETR : Modulated Detection for End-to-End Multi-Modal Understanding
https://www.zhuanzhi.ai/paper/945f0402f0332c41872bb7869e490be3
3. 稠密对应无监督学习,Warp Consistency for Unsupervised Learning of Dense Correspondenceshttps://www.zhuanzhi.ai/paper/678dd14c5c3ed4b6ab0c4c782ed0f135
4. 目标检测和实例分割的Rank & Sort损失,Rank & Sort Loss for Object Detection and Instance Segmentationhttps://arxiv.org/abs/2002.122135. 递归条件高斯的有序无监督域自适应, Recursively Conditional Gaussian for Ordinal Unsupervised Domain Adaptationhttps://www.zhuanzhi.ai/paper/64e91d0014516f1556b0b8101808d141
6. SimROD:一种简单的鲁棒目标检测自适应方法,SimROD: A Simple Adaptation Method for Robust Object Detectionhttps://www.zhuanzhi.ai/paper/5ddf35892e95179e384ff22f84e52821
7. 残差对数似然估计的人体姿态回归,Human Pose Regression with Residual Log-likelihood Estimationhttps://www.zhuanzhi.ai/paper/e029b16a9f5bdfbf2b83993a1e4d3be2
8. 无监督域适应的运输因果机制,Transporting Causal Mechanisms for Unsupervised Domain Adaptationhttps://www.zhuanzhi.ai/paper/57f86ec4e25735fa6a744ec9d17478519. 深度假检测的自一致性学习,Learning Self-Consistency for Deepfake Detectionhttps://www.zhuanzhi.ai/paper/5115974ee34bc53b0e76fce5b5f5b26410. 自监督对应学习,Rethinking Self-supervised Correspondence Learning: A Video Frame-level Similarity Perspectivehttps://www.zhuanzhi.ai/paper/57095349f92f887dd0c496af3986197e11. 研究语义分割中无监督领域自适应的鲁棒性,Exploring Robustness of Unsupervised Domain Adaptation in Semantic Segmentationhttps://www.zhuanzhi.ai/paper/0b6a434549580ea778cdf816522b5784
12. 用于稳健姿态估计的三维人体运动模型,HuMoR: 3D Human Motion Model for Robust Pose Estimationhttps://www.zhuanzhi.ai/paper/9f76eaa62f8a456a6acddb107e1c1569
13. 半监督语义分割,Re-distributing Biased Pseudo Labels for Semi-supervised Semantic Segmentation: A Baseline Investigationhttps://www.zhuanzhi.ai/paper/8400abaa3b0718f15fdf5b531c86eeda
14. 通过跨域集成的鲁棒性,Robustness via Cross-Domain Ensembleshttps://www.zhuanzhi.ai/paper/2ab2815739ff76f5e17ac41dbb537175
15. 弱监督物体定位路由再思考,Just Ask: Learning to Answer Questions from Millions of Narrated Videoshttps://www.zhuanzhi.ai/paper/fe5d9d7861cec92597a33dbf3178d776