297 citations · 2.2k across the 85 of their papers we have counts for
39 papers · 1 filter
Dynamic Multimodal Fusion via Meta-Learning Towards Micro-Video Recommendation
Han Liu, Yinwei Wei, Fan Liu +3
Multimodal information (e.g., visual, acoustic, and textual) has been widely used to enhance representation learning for micro-video recommendation. For integrating multimodal info…
Detecting and Grounding Multi-Modal Media Manipulation and Beyond
Rui Shao, Tianxing Wu, Jianlong Wu +2
Misinformation has become a pressing issue. Fake media, in both visual and textual forms, is widespread on the web. While various deepfake detection and text fake news detection me…
Temporal Sentence Grounding in Streaming Videos
Tian Gan, Xiao Wang, Yan Sun +3
This paper aims to tackle a novel task - Temporal Sentence Grounding in Streaming Videos (TSGSV). The goal of TSGSV is to evaluate the relevance between a video stream and a given…
LayoutLLM-T2I: Eliciting Layout Guidance from LLM for Text-to-Image Generation
Leigang Qu, Shengqiong Wu, Hao Fei +2
In the text-to-image generation field, recent remarkable progress in Stable Diffusion makes it possible to generate rich kinds of novel photorealistic images. However, current mode…
StyleEDL: Style-Guided High-order Attention Network for Image Emotion Distribution Learning
Peiguang Jing, Xianyi Liu, Ji Wang +3
Emotion distribution learning has gained increasing attention with the tendency to express emotions through images. As for emotion ambiguity arising from humans' subjectivity, subs…
Towards Generalizable Deepfake Detection by Primary Region Regularization
Harry Cheng, Yangyang Guo, Tianyi Wang +2
The existing deepfake detection methods have reached a bottleneck in generalizing to unseen forgeries and manipulation approaches. Based on the observation that the deepfake detect…
Sample Less, Learn More: Efficient Action Recognition via Frame Feature Restoration
Harry Cheng, Yangyang Guo, Liqiang Nie +2
Training an effective video action recognition model poses significant computational challenges, particularly under limited resource budgets. Current methods primarily aim to eithe…
A Survey on Video Moment Localization
Meng Liu, Liqiang Nie, Yunxiao Wang +2
Video moment localization, also known as video moment retrieval, aiming to search a target segment within a video described by a given natural language query. Beyond the task of te…
DeepFake-Adapter: Dual-Level Adapter for DeepFake Detection
Rui Shao, Tianxing Wu, Liqiang Nie +1
Existing deepfake detection methods fail to generalize well to unseen or degraded samples, which can be attributed to the over-fitting of low-level forgery patterns. Here we argue…
RaSa: Relation and Sensitivity Aware Representation Learning for Text-based Person Search
Yang Bai, Min Cao, Daming Gao +5
Text-based person search aims to retrieve the specified person images given a textual description. The key to tackling such a challenging task is to learn powerful multi-modal repr…
Text-based Person Search without Parallel Image-Text Data
Yang Bai, Jingyao Wang, Min Cao +4
Text-based person search (TBPS) aims to retrieve the images of the target person from a large image gallery based on a given natural language description. Existing methods are domi…
Learnable Pillar-based Re-ranking for Image-Text Retrieval
Leigang Qu, Meng Liu, Wenjie Wang +3
Image-text retrieval aims to bridge the modality gap and retrieve cross-modal content based on semantic similarities. Prior work usually focuses on the pairwise relations (i.e., wh…
Revisiting Context Aggregation for Image Matting
Qinglin Liu, Xiaoqian Lv, Quanling Meng +5
Traditional studies emphasize the significance of context information in improving matting performance. Consequently, deep learning-based matting methods delve into designing pooli…
Efficient Image-Text Retrieval via Keyword-Guided Pre-Screening
Min Cao, Yang Bai, Jingyao Wang +3
Under the flourishing development in performance, current image-text retrieval methods suffer from -related time complexity, which hinders their application in practice. Targeti…
Reliable Representation Learning for Incomplete Multi-View Missing Multi-Label Classification
Chengliang Liu, Jie Wen, Yong Xu +3
As a cross-topic of multi-view learning and multi-label classification, multi-view multi-label classification has gradually gained traction in recent years. The application of mult…
Learning to Agree on Vision Attention for Visual Commonsense Reasoning
Zhenyang Li, Yangyang Guo, Kejie Wang +3
Visual Commonsense Reasoning (VCR) remains a significant yet challenging research problem in the realm of visual reasoning. A VCR model generally aims at answering a textual questi…
Multi-queue Momentum Contrast for Microvideo-Product Retrieval
Yali Du, Yinwei Wei, Wei Ji +3
The booming development and huge market of micro-videos bring new e-commerce channels for merchants. Currently, more micro-video publishers prefer to embed relevant ads into their…
Deep Convolutional Pooling Transformer for Deepfake Detection
Tianyi Wang, Harry Cheng, Kam Pui Chow +1
Recently, Deepfake has drawn considerable public attention due to security and privacy concerns in social media digital forensics. As the wildly spreading Deepfake videos on the In…
Visual Perturbation-aware Collaborative Learning for Overcoming the Language Prior Problem
Yudong Han, Liqiang Nie, Jianhua Yin +2
Several studies have recently pointed that existing Visual Question Answering (VQA) models heavily suffer from the language prior problem, which refers to capturing superficial sta…
Semantic-aware Modular Capsule Routing for Visual Question Answering
Yudong Han, Jianhua Yin, Jianlong Wu +2
Visual Question Answering (VQA) is fundamentally compositional in nature, and many questions are simply answered by decomposing them into modular sub-problems. The recent proposed…
Network Binarization via Contrastive Learning
Yuzhang Shang, Dan Xu, Ziliang Zong +2
Neural network binarization accelerates deep models by quantizing their weights and activations into 1-bit. However, there is still a huge performance gap between Binary Neural Net…
A Unified End-to-End Retriever-Reader Framework for Knowledge-based VQA
Yangyang Guo, Liqiang Nie, Yongkang Wong +3
Knowledge-based Visual Question Answering (VQA) expects models to rely on external knowledge for robust answer prediction. Though significant it is, this paper discovers several le…
Stacked Hybrid-Attention and Group Collaborative Learning for Unbiased Scene Graph Generation
Xingning Dong, Tian Gan, Xuemeng Song +3
Scene Graph Generation, which generally follows a regular encoder-decoder pipeline, aims to first encode the visual contents within the given image and then parse them into a compa…
Voice-Face Homogeneity Tells Deepfake
Harry Cheng, Yangyang Guo, Tianyi Wang +3
Detecting forgery videos is highly desirable due to the abuse of deepfake. Existing detection approaches contribute to exploring the specific artifacts in deepfake videos and fit w…