1.5k citations
Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.
- National University of SingaporeSG206 papers
- Nanyang Technological UniversitySG120 papers
- Centre for Quantum TechnologiesSG107 papers
- Agency for Science, Technology and ResearchSG70 papers
- Zhejiang UniversityCN67 papers
- Beihang UniversityCN61 papers
- Beijing Institute of TechnologyCN59 papers
- Massachusetts Institute of TechnologyUS42 papers
- Centre National de la Recherche ScientifiqueFR33 papers
- UMI MajuLabSG33 papers
- Hunan Normal UniversityCN32 papers
- Institute of High Performance ComputingSG31 papers
68 papers · 1 filter
When Visual Privacy Protection Meets Multimodal Large Language Models
Xiaofei Hui, Qian Wu, Haoxuan Qu +3
The emergence of Multimodal Large Language Models (MLLMs) and the widespread usage of MLLM cloud services such as GPT-4V raised great concerns about privacy leakage in visual data.…
A 96pJ/Frame/Pixel and 61pJ/Event Anti-UAV System with Hybrid Object Tracking Modes
Yuncheng Lu, Yucen Shi, Aobo Li +4
We present an energy-efficient anti-UAV system that integrates frame-based and event-driven object tracking to enable reliable detection of small and fast-moving drones. The system…
Dual-supervised Asymmetric Co-training for Semi-supervised Medical Domain Generalization
Jincai Song, Haipeng Chen, Jun Qin +1
Semi-supervised domain generalization (SSDG) in medical image segmentation offers a promising solution for generalizing to unseen domains during testing, addressing domain shift ch…
HateClipSeg: A Segment-Level Annotated Dataset for Fine-Grained Hate Video Detection
Han Wang, Zhuoran Wang, Roy Ka-Wei Lee
Detecting hate speech in videos remains challenging due to the complexity of multimodal content and the lack of fine-grained annotations in existing datasets. We present HateClipSe…
Analyzing Swimming Performance Using Drone Captured Aerial Videos
Thu Tran, Kenny Tsu Wei Choo, Shaohui Foong +5
Monitoring swimmer performance is crucial for improving training and enhancing athletic techniques. Traditional methods for tracking swimmers, such as above-water and underwater ca…
Cross-Modal Transfer from Memes to Videos: Addressing Data Scarcity in Hateful Video Detection
Han Wang, Rui Yang Tan, Roy Ka-Wei Lee
Detecting hate speech in online content is essential to ensuring safer digital spaces. While significant progress has been made in text and meme modalities, video-based hate speech…
On-the-fly Point Feature Representation for Point Clouds Analysis
Jiangyi Wang, Zhongyao Cheng, Na Zhao +2
Point cloud analysis is challenging due to its unique characteristics of unorderness, sparsity and irregularity. Prior works attempt to capture local relationships by convolution o…
SoccerNet 2023 Challenges Results
Anthony Cioppa, Silvio Giancola, Vladimir Somers +99
The SoccerNet 2023 challenges were the third annual video understanding challenges organized by the SoccerNet team. For this third edition, the challenges were composed of seven vi…
GenKL: An Iterative Framework for Resolving Label Ambiguity and Label Non-conformity in Web Images Via a New Generalized KL Divergence
Xia Huang, Kai Fong Ernest Chong
Web image datasets curated online inherently contain ambiguous in-distribution (ID) instances and out-of-distribution (OOD) instances, which we collectively call non-conforming (NC…
Distribution-aware Fairness Test Generation
Sai Sathiesh Rajan, Ezekiel Soremekun, Yves Le Traon +1
Ensuring that all classes of objects are detected with equal accuracy is essential in AI systems. For instance, being unable to identify any one class of objects could have fatal c…
FVP: Fourier Visual Prompting for Source-Free Unsupervised Domain Adaptation of Medical Image Segmentation
Yan Wang, Jian Cheng, Yixin Chen +5
Medical image segmentation methods normally perform poorly when there is a domain shift between training and testing data. Unsupervised Domain Adaptation (UDA) addresses the domain…
Precise Facial Landmark Detection by Reference Heatmap Transformer
Jun Wan, Jun Liu, Jie Zhou +5
Most facial landmark detection methods predict landmarks by mapping the input facial appearance features to landmark heatmaps and have achieved promising results. However, when the…
FS-BAN: Born-Again Networks for Domain Generalization Few-Shot Classification
Yunqing Zhao, Ngai-Man Cheung
Conventional Few-shot classification (FSC) aims to recognize samples from novel classes given limited labeled data. Recently, domain generalization FSC (DG-FSC) has been proposed w…
Incremental Few-Shot Semantic Segmentation via Embedding Adaptive-Update and Hyper-class Representation
Guangchen Shi, Yirui Wu, Jun Liu +3
Incremental few-shot semantic segmentation (IFSS) targets at incrementally expanding model's capacity to segment new class of images supervised by only a few samples. However, feat…
Towards Class-agnostic Tracking Using Feature Decorrelation in Point Clouds
Shengjing Tian, Jun Liu, Xiuping Liu
Single object tracking in point clouds has been attracting more and more attention owing to the presence of LiDAR sensors in 3D vision. However, the existing methods based on deep…
Predicting emotion from music videos: exploring the relative contribution of visual and auditory information to affective responses
Phoebe Chua, Dimos Makris, Dorien Herremans +2
Although media content is increasingly produced, distributed, and consumed in multiple combinations of modalities, how individual modalities contribute to the perceived emotion of…
KTNet: Knowledge Transfer for Unpaired 3D Shape Completion
Zhen Cao, Wenxiao Zhang, Xin Wen +4
Unpaired 3D object completion aims to predict a complete 3D shape from an incomplete input without knowing the correspondence between the complete and incomplete shapes. In this pa…
Conterfactual Generative Zero-Shot Semantic Segmentation
Feihong Shen, Jun Liu, Ping Hu
zero-shot learning is an essential part of computer vision. As a classical downstream task, zero-shot semantic segmentation has been studied because of its applicant value. One of…
UAV-Human: A Large Benchmark for Human Behavior Understanding with Unmanned Aerial Vehicles
Tianjiao Li, Jun Liu, Wei Zhang +3
Human behavior understanding with unmanned aerial vehicles (UAVs) is of great significance for a wide range of applications, which simultaneously brings an urgent demand of large,…
A Closer Look at Fourier Spectrum Discrepancies for CNN-generated Images Detection
Keshigeyan Chandrasegaran, Ngoc-Trung Tran, Ngai-Man Cheung
CNN-based generative modelling has evolved to produce synthetic images indistinguishable from real images in the RGB pixel space. Recent works have observed that CNN-generated imag…
Dual-Refinement: Joint Label and Feature Refinement for Unsupervised Domain Adaptive Person Re-Identification
Yongxing Dai, Jun Liu, Yan Bai +2
Unsupervised domain adaptive (UDA) person re-identification (re-ID) is a challenging task due to the missing of labels for the target domain data. To handle this problem, some rece…
Direct Quantization for Training Highly Accurate Low Bit-width Deep Neural Networks
Tuan Hoang, Thanh-Toan Do, Tam V. Nguyen +1
This paper proposes two novel techniques to train deep convolutional neural networks with low bit-width weights and activations. First, to obtain low bit-width weights, most existi…
Human Action Recognition from Various Data Modalities: A Review
Zehua Sun, Qiuhong Ke, Hossein Rahmani +3
Human Action Recognition (HAR) aims to understand human behavior and assign a label to each action. It has a wide range of applications, and therefore has been attracting increasin…
Skeleton-based Relational Reasoning for Group Activity Analysis
Mauricio Perez, Jun Liu, Alex C. Kot
Research on group activity recognition mostly leans on the standard two-stream approach (RGB and Optical Flow) as their input features. Few have explored explicit pose information,…