44 citations · 191 across the 34 of their papers we have counts for
8 papers · 1 filter
Generalizable Re-Identification from Videos with Cycle Association
Zhongdao Wang, Zhaopeng Dou, Jingwei Zhang +4
In this paper, we are interested in learning a generalizable person re-identification (re-ID) representation from unlabeled videos. Compared with 1) the popular unsupervised re-ID…
Reliability-Aware Prediction via Uncertainty Learning for Person Image Retrieval
Zhaopeng Dou, Zhongdao Wang, Weihua Chen +2
Current person image retrieval methods have achieved great improvements in accuracy metrics. However, they rarely describe the reliability of the prediction. In this paper, we prop…
Self-Supervised Learning via Maximum Entropy Coding
Xin Liu, Zhongdao Wang, Yali Li +1
A mainstream type of current self-supervised learning methods pursues a general-purpose representation that can be well transferred to downstream tasks, typically by optimizing on…
GraphCSPN: Geometry-Aware Depth Completion via Dynamic GCNs
Xin Liu, Xiaofei Shao, Bo Wang +2
Image guided depth completion aims to recover per-pixel dense depth maps from sparse depth measurements with the help of aligned color images, which has a wide range of application…
Portrait Interpretation and a Benchmark
Yixuan Fan, Zhaopeng Dou, Yali Li +1
We propose a task we name Portrait Interpretation and construct a dataset named Portrait250K for it. Current researches on portraits such as human attribute recognition and person…
Hybrid Physical Metric For 6-DoF Grasp Pose Detection
Yuhao Lu, Beixing Deng, Zhenyu Wang +3
6-DoF grasp pose detection of multi-grasp and multi-object is a challenge task in the field of intelligent robot. To imitate human reasoning ability for grasping objects, data driv…
R(Det)^2: Randomized Decision Routing for Object Detection
Ya-Li Li, Shengjin Wang
In the paradigm of object detection, the decision head is an important part, which affects detection performance significantly. Yet how to design a high-performance decision head r…
Noisy Boundaries: Lemon or Lemonade for Semi-supervised Instance Segmentation?
Zhenyu Wang, Yali Li, Shengjin Wang
Current instance segmentation methods rely heavily on pixel-level annotated images. The huge cost to obtain such fully-annotated images restricts the dataset scale and limits the p…