649 citations · 1.8k across the 42 of their papers we have counts for
13 papers · 1 filter
Learning Active Camera for Multi-Object Navigation
Peihao Chen, Dongyu Ji, Kunyang Lin +5
Getting robots to navigate to multiple objects autonomously is essential yet difficult in robot applications. One of the key challenges is how to explore environments efficiently w…
Smoothing Matters: Momentum Transformer for Domain Adaptive Semantic Segmentation
Runfa Chen, Yu Rong, Shangmin Guo +4
After the great success of Vision Transformer variants (ViTs) in computer vision, it has also demonstrated great potential in domain adaptive semantic segmentation. Unfortunately,…
Sim2Real Object-Centric Keypoint Detection and Description
Chengliang Zhong, Chao Yang, Jinshan Qi +4
Keypoint detection and description play a central role in computer vision. Most existing methods are in the form of scene-level prediction, without returning the object classes of…
Channel Exchanging Networks for Multimodal and Multitask Dense Image Prediction
Yikai Wang, Fuchun Sun, Wenbing Huang +2
Multimodal fusion and multitask learning are two vital topics in machine learning. Despite the fruitful progress, existing methods for both problems are still brittle to the same c…
Graph Convolutional Module for Temporal Action Localization in Videos
Runhao Zeng, Wenbing Huang, Mingkui Tan +4
Temporal action localization has long been researched in computer vision. Existing state-of-the-art action localization methods divide each video into multiple action units (i.e.,…
Deep Multimodal Fusion by Channel Exchanging
Yikai Wang, Wenbing Huang, Fuchun Sun +3
Deep multimodal fusion by using multiple sources of data for classification or regression has exhibited a clear advantage over the unimodal counterpart on various applications. Yet…
Towards Purely Unsupervised Disentanglement of Appearance and Shape for Person Images Generation
Hongtao Yang, Tong Zhang, Wenbing Huang +2
There have been a fairly of research interests in exploring the disentanglement of appearance and shape from human images. Most existing endeavours pursuit this goal by either usin…
Dense Regression Network for Video Grounding
Runhao Zeng, Haoming Xu, Wenbing Huang +3
We address the problem of video grounding from natural language queries. The key challenge in this task is that one training video might only contain a few annotated starting/endin…
Reusing Discriminators for Encoding: Towards Unsupervised Image-to-Image Translation
Runfa Chen, Wenbing Huang, Binghui Huang +2
Unsupervised image-to-image translation is a central task in computer vision. Current translation frameworks will abandon the discriminator once the training process is completed.…
Graph Convolutional Networks for Temporal Action Localization
Runhao Zeng, Wenbing Huang, Mingkui Tan +4
Most state-of-the-art action localization systems process each action proposal individually, without explicitly exploiting their relations during learning. However, the relations b…
A Fast and Accurate One-Stage Approach to Visual Grounding
Zhengyuan Yang, Boqing Gong, Liwei Wang +3
We propose a simple, fast, and accurate one-stage approach to visual grounding, inspired by the following insight. The performances of existing propose-and-rank two-stage methods a…
Progressive Feature Alignment for Unsupervised Domain Adaptation
Chaoqi Chen, Weiping Xie, Wenbing Huang +5
Unsupervised domain adaptation (UDA) transfers knowledge from a label-rich source domain to a fully-unlabeled target domain. To tackle this task, recent approaches resort to discri…
Generalized Zero-Shot Learning for Action Recognition with Web-Scale Video Data
Kun Liu, Wu Liu, Huadong Ma +2
Action recognition in surveillance video makes our life safer by detecting the criminal events or predicting violent emergencies. However, efficient action recognition is not free…