activity
20182022
most citedBi-directional Dermoscopic Feature Learning and Multi-scale Consistent Decision Fusion for Skin Lesion Segmentation

85 citations · 182 across the 10 of their papers we have counts for

collaborators

13 papers

cs.CV202264 cited

Instance-Specific Feature Propagation for Referring Segmentation

Chang Liu, Xudong Jiang, Henghui Ding

Referring segmentation aims to generate a segmentation mask for the target instance indicated by a natural language expression. There are typically two kinds of existing methods: o…

cs.CV202116 cited

Vision-Language Transformer and Query Generation for Referring Segmentation

Henghui Ding, Chang Liu, Suchen Wang +1

In this work, we address the challenging task of referring segmentation. The query expression in referring segmentation typically indicates the target object by describing its rela…

cs.CV2021

Towards Enhancing Fine-grained Details for Image Matting

Chang Liu, Henghui Ding, Xudong Jiang

In recent years, deep natural image matting has been rapidly evolved by extracting high-level contextual features into the model. However, most current methods still have difficult…

cs.LG20201 cited

Feature Distillation With Guided Adversarial Contrastive Learning

Tao Bai, Jinnan Chen, Jun Zhao +3

Deep learning models are shown to be vulnerable to adversarial examples. Though adversarial training can enhance model robustness, typical approaches are computationally expensive.…

cs.CV20207 cited

Temporal Distinct Representation Learning for Action Recognition

Junwu Weng, Donghao Luo, Yabiao Wang +6

Motivated by the previous success of Two-Dimensional Convolutional Neural Network (2D CNN) on image recognition, researchers endeavor to leverage it to characterize videos. However…

cs.CV20201 cited

Object 6D Pose Estimation with Non-local Attention

Jianhan Mei, Henghui Ding, Xudong Jiang

In this paper, we address the challenging task of estimating 6D object pose from a single RGB image. Motivated by the deep learning based object detection methods, we propose a con…