17 citations · 51 across the 16 of their papers we have counts for
16 papers
BAVS: Bootstrapping Audio-Visual Segmentation by Integrating Foundation Knowledge
Chen Liu, Peike Li, Hu Zhang +4
Given an audio-visual pair, audio-visual segmentation (AVS) aims to locate sounding sources by predicting pixel-wise maps. Previous methods assume that each sound component in an a…
Audio-Visual Segmentation by Exploring Cross-Modal Mutual Semantics
Chen Liu, Peike Li, Xingqun Qi +4
The audio-visual segmentation (AVS) task aims to segment sounding objects from a given video. Existing works mainly focus on fusing audio and visual features of a given video to ac…
Unleashing the Potential of Regularization Strategies in Learning with Noisy Labels
Hui Kang, Sheng Liu, Huaxi Huang +4
In recent years, research on learning with noisy labels has focused on devising novel algorithms that can achieve robustness to noisy training labels while generalizing to clean da…
ESceme: Vision-and-Language Navigation with Episodic Scene Memory
Qi Zheng, Daqing Liu, Chaoyue Wang +3
Vision-and-language navigation (VLN) simulates a visual agent that follows natural-language navigation instructions in real-world scenes. Existing approaches have made enormous pro…
PADDLES: Phase-Amplitude Spectrum Disentangled Early Stopping for Learning with Noisy Labels
Huaxi Huang, Hui Kang, Sheng Liu +4
Convolutional Neural Networks (CNNs) have demonstrated superiority in learning patterns, but are sensitive to label noises and may overfit noisy labels during training. The early s…
Cross-Modal Contrastive Learning for Robust Reasoning in VQA
Qi Zheng, Chaoyue Wang, Daqing Liu +2
Multi-modal reasoning in visual question answering (VQA) has witnessed rapid progress recently. However, most reasoning models heavily rely on shortcuts learned from training data,…
CNN-based Local Vision Transformer for COVID-19 Diagnosis
Hongyan Xu, Xiu Su, Dadong Wang
Deep learning technology can be used as an assistive technology to help doctors quickly and accurately identify COVID-19 infections. Recently, Vision Transformer (ViT) has shown gr…
Multi-scale alignment and Spatial ROI Module for COVID-19 Diagnosis
Hongyan Xu, Dadong Wang, Arcot Sowmya
Coronavirus Disease 2019 (COVID-19) has spread globally and become a health crisis faced by humanity since first reported. Radiology imaging technologies such as computer tomograph…
Bypass Network for Semantics Driven Image Paragraph Captioning
Qi Zheng, Chaoyue Wang, Dadong Wang
Image paragraph captioning aims to describe a given image with a sequence of coherent sentences. Most existing methods model the coherence through the topic transition that dynamic…
MSR: Making Self-supervised learning Robust to Aggressive Augmentations
Yingbin Bai, Erkun Yang, Zhaoqing Wang +5
Most recent self-supervised learning methods learn visual representation by contrasting different augmented views of images. Compared with supervised learning, more aggressive augm…
Visual Superordinate Abstraction for Robust Concept Learning
Qi Zheng, Chaoyue Wang, Dadong Wang +1
Concept learning constructs visual representations that are connected to linguistic semantics, which is fundamental to vision-language tasks. Although promising progress has been m…
Monitoring of Pigmented Skin Lesions Using 3D Whole Body Imaging
David Ahmedt-Aristizabal, Chuong Nguyen, Lachlan Tychsen-Smith +5
Advanced artificial intelligence and machine learning have great potential to redefine how skin lesions are detected, mapped, tracked and documented. Here, We propose a 3D whole-bo…
Computer-Aided Extraction of Select MRI Markers of Cerebral Small Vessel Disease: A Systematic Review
Jiyang Jiang, Dadong Wang, Yang Song +2
Cerebral small vessel disease (CSVD) is a major vascular contributor to cognitive impairment in ageing, including dementias. Imaging remains the most promising method for in vivo s…
PDANet: Pyramid Density-aware Attention Net for Accurate Crowd Counting
Saeed Amirgholipour, Xiangjian He, Wenjing Jia +2
Crowd counting, i.e., estimating the number of people in a crowded area, has attracted much interest in the research community. Although many attempts have been reported, crowd cou…
A-CCNN: adaptive ccnn for density estimation and crowd counting
Saeed Amirgholipour Kasmani, Xiangjian He, Wenjing Jia +2
Crowd counting, for estimating the number of people in a crowd using vision-based computer techniques, has attracted much interest in the research community. Although many attempts…
A Structural Correlation Filter Combined with A Multi-task Gaussian Particle Filter for Visual Tracking
Manna Dai, Shuying Cheng, Xiangjian He +1
In this paper, we propose a novel structural correlation filter combined with a multi-task Gaussian particle filter (KCF-GPF) model for robust visual tracking. We first present an…