activity
20192026
most citedContext-aware Biaffine Localizing Network for Temporal Sentence Grounding

15 citations · 102 across the 35 of their papers we have counts for

collaborators

40 papers

cs.CV2026

RFMSR: Residual Flow Matching for Image Super-Resolution

Shuwei Huang, Tianyao Luo, Jicheng Liu +1

Image super-resolution (ISR) has witnessed remarkable progress with diffusion models and flow matching. The dominant text-to-image (T2I) based approaches leverage large-scale found…

cs.CV2026

Annotations Are Not All You Need: A Cross-modal Knowledge Transfer Network for Unsupervised Temporal Sentence Grounding

Xiang Fang, Daizong Liu, Wanlong Fang +4

This paper addresses the task of temporal sentence grounding (TSG). Although many respectable works have made decent achievements in this important topic, they severely rely on mas…

cs.CV2026

Not All Inputs Are Valid: Towards Open-Set Video Moment Retrieval Using Language

Xiang Fang, Wanlong Fang, Daizong Liu +8

Video Moment Retrieval (VMR) targets to retrieve the specific moment corresponding to a sentence query from an untrimmed video. Although recent works have made remarkable progress…

cs.CV2026

Fewer Steps, Better Performance: Efficient Cross-Modal Clip Trimming for Video Moment Retrieval Using Language

Xiang Fang, Daizong Liu, Wanlong Fang +5

Given an untrimmed video and a sentence query, video moment retrieval using language (VMR) aims to locate a target query-relevant moment. Since the untrimmed video is overlong, alm…

cs.CV2026

Rethinking Weakly-supervised Video Temporal Grounding From a Game Perspective

Xiang Fang, Zeyu Xiong, Wanlong Fang +7

This paper addresses the challenging task of weakly-supervised video temporal grounding. Existing approaches are generally based on the moment proposal selection framework that uti…

cs.AI2026

AutoResearch AI: Towards AI-Powered Research Automation for Scientific Discovery

Guiyao Tie, Jiawen Shi, Dingjie Song +20

Scientific research is being reshaped by AI systems that move beyond isolated assistance toward longer-horizon workflows spanning literature grounding, hypothesis generation, exper…

cs.CV2025

An Image Is Worth Ten Thousand Words: Verbose-Text Induction Attacks on VLMs

Zhi Luo, Zenghui Yuan, Wenqi Wei +2

With the remarkable success of Vision-Language Models (VLMs) on multimodal tasks, concerns regarding their deployment efficiency have become increasingly prominent. In particular,…

cs.CR2025

Learning from Few Samples: A Novel Approach for High-Quality Malcode Generation

Haijian Ma, Daizong Liu, Xiaowen Cai +2

Intrusion Detection Systems (IDS) play a crucial role in network security defense. However, a significant challenge for IDS in training detection models is the shortage of adequate…

cs.CV2024

Multi-Pair Temporal Sentence Grounding via Multi-Thread Knowledge Transfer Network

Xiang Fang, Wanlong Fang, Changshuo Wang +5

Given some video-query pairs with untrimmed videos and sentence queries, temporal sentence grounding (TSG) aims to locate query-relevant segments in these videos. Although previous…

cs.CV2024

Hard-Label Black-Box Attacks on 3D Point Clouds

Daizong Liu, Yunbo Tao, Junhao Dong +4

With the maturity of depth sensors in various 3D safety-critical applications, 3D point cloud models have been shown to be vulnerable to adversarial attacks. Almost all existing 3D…

cs.CV2024★ 1 cited

A Survey of Attacks on Large Vision-Language Models: Resources, Advances, and Future Trends

Daizong Liu, Mingyu Yang, Xiaoye Qu +3

With the significant development of large models in recent years, Large Vision-Language Models (LVLMs) have demonstrated remarkable capabilities across a wide range of multimodal u…

cs.CV2023

Unified Multi-modal Unsupervised Representation Learning for Skeleton-based Action Understanding

Shengkai Sun, Daizong Liu, Jianfeng Dong +5

Unsupervised pre-training has shown great success in skeleton-based action understanding recently. Existing works typically train separate modality-specific models, then integrate…

cs.CV2023★ 2 cited

3DHacker: Spectrum-based Decision Boundary Generation for Hard-label 3D Point Cloud Attack

Yunbo Tao, Daizong Liu, Pan Zhou +3

With the maturity of depth sensors, the vulnerability of 3D point cloud models has received increasing attention in various applications such as autonomous driving and robot naviga…

cs.CV2023★ 12 cited

From Region to Patch: Attribute-Aware Foreground-Background Contrastive Learning for Fine-Grained Fashion Retrieval

Jianfeng Dong, Xiaoman Peng, Zhe Ma +5

Attribute-specific fashion retrieval (ASFR) is a challenging information retrieval task, which has attracted increasing attention in recent years. Different from traditional fashio…

cs.CV2023★ 2 cited

Transform-Equivariant Consistency Learning for Temporal Sentence Grounding

Daizong Liu, Xiaoye Qu, Jianfeng Dong +6

This paper addresses the temporal sentence grounding (TSG). Although existing methods have made decent achievements in this task, they not only severely rely on abundant video-quer…

cs.CV2023★ 3 cited

Density-Insensitive Unsupervised Domain Adaption on 3D Object Detection

Qianjiang Hu, Daizong Liu, Wei Hu

3D object detection from point clouds is crucial in safety-critical autonomous driving. Although many works have made great efforts and achieved significant progress on this task,…

cs.CV2023

Jointly Visual- and Semantic-Aware Graph Memory Networks for Temporal Sentence Localization in Videos

Daizong Liu, Pan Zhou

Temporal sentence localization in videos (TSLV) aims to retrieve the most interested segment in an untrimmed video according to a given sentence query. However, almost of existing…

cs.CV2023★ 6 cited

You Can Ground Earlier than See: An Effective and Efficient Pipeline for Temporal Sentence Grounding in Compressed Videos

Xiang Fang, Daizong Liu, Pan Zhou +1

Given an untrimmed video, temporal sentence grounding (TSG) aims to locate a target moment semantically according to a sentence query. Although previous respectable works have made…

cs.CV2023

Tracking Objects and Activities with Attention for Temporal Sentence Grounding

Zeyu Xiong, Daizong Liu, Pan Zhou +1

Temporal sentence grounding (TSG) aims to localize the temporal segment which is semantically aligned with a natural language query in an untrimmed video.Most existing methods extr…

cs.CV2023★ 3 cited

Hypotheses Tree Building for One-Shot Temporal Sentence Localization

Daizong Liu, Xiang Fang, Pan Zhou +3

Given an untrimmed video, temporal sentence localization (TSL) aims to localize a specific segment according to a given sentence query. Though respectable works have made decent ac…

cs.CV2023

Rethinking the Video Sampling and Reasoning Strategies for Temporal Sentence Grounding

Jiahao Zhu, Daizong Liu, Pan Zhou +8

Temporal sentence grounding (TSG) aims to identify the temporal boundary of a specific segment from an untrimmed video by a sentence query. All existing works first utilize a spars…

cs.CL2022★ 2 cited

Distantly-Supervised Named Entity Recognition with Adaptive Teacher Learning and Fine-grained Student Ensemble

Xiaoye Qu, Jun Zeng, Daizong Liu +3

Distantly-Supervised Named Entity Recognition (DS-NER) effectively alleviates the data scarcity problem in NER by automatically generating training samples. Unfortunately, the dist…

cs.CV2022★ 7 cited

Multi-Modal Cross-Domain Alignment Network for Video Moment Retrieval

Xiang Fang, Daizong Liu, Pan Zhou +1

As an increasingly popular task in multimedia information retrieval, video moment retrieval (VMR) aims to localize the target moment from an untrimmed video according to a given la…

cs.MM2022★ 5 cited

Hierarchical Local-Global Transformer for Temporal Sentence Grounding

Xiang Fang, Daizong Liu, Pan Zhou +2

This paper studies the multimedia problem of temporal sentence grounding (TSG), which aims to accurately determine the specific video segment in an untrimmed video according to a g…