activity
20182022
most citedMotion-Focused Contrastive Learning of Video Representations

4 citations · 10 across the 4 of their papers we have counts for

collaborators

8 papers

cs.CV20221 cited

Explaining Cross-Domain Recognition with Interpretable Deep Classifier

Yiheng Zhang, Ting Yao, Zhaofan Qiu +1

The recent advances in deep learning predominantly construct models in their internal representations, and it is opaque to explain the rationale behind and decisions to human users…

cs.CV20224 cited

Motion-Focused Contrastive Learning of Video Representations

Rui Li, Yiheng Zhang, Zhaofan Qiu +3

Motion, as the most distinct phenomenon in a video to involve the changes over time, has been unique and critical to the development of video representation learning. In this paper…

cs.CV2020

SeCo: Exploring Sequence Supervision for Unsupervised Representation Learning

Ting Yao, Yiheng Zhang, Zhaofan Qiu +2

A steady momentum of innovations and breakthroughs has convincingly pushed the limits of unsupervised image representation learning. Compared to static 2D images, video has one mor…

cs.CV20202 cited

Transferring and Regularizing Prediction for Semantic Segmentation

Yiheng Zhang, Zhaofan Qiu, Ting Yao +3

Semantic segmentation often requires a large set of images with pixel-level annotations. In the view of extremely expensive expert labeling, recent research has shown that the mode…

cs.CV20193 cited

Scheduled Differentiable Architecture Search for Visual Recognition

Zhaofan Qiu, Ting Yao, Yiheng Zhang +2

Convolutional Neural Networks (CNN) have been regarded as a capable class of models for visual recognition problems. Nevertheless, it is not trivial to develop generic and powerful…

cs.CV2019

Customizable Architecture Search for Semantic Segmentation

Yiheng Zhang, Zhaofan Qiu, Jingen Liu +3

In this paper, we propose a Customizable Architecture Search (CAS) approach to automatically generate a network architecture for semantic image segmentation. The generated network…