9 citations · 21 across the 21 of their papers we have counts for
10 papers · 1 filter
Improving Adversarial Transferability on Vision-Language Pre-training Models via Surrogate-Specific Bias Correction
Lijia Yu, Jiuxin Cao, Yuchen Qiang +3
Adversarial examples reveal vulnerabilities in Vision-Language Pre-training (VLP) models and provide insights for improving robustness. A key property is cross-model transferabilit…
ViewSAM: Learning View-aware Cross-modal Semantics for Weakly Supervised Cross-view Referring Multi-Object Tracking
Jiawei Ge, Xintian Zhang, Jiuxin Cao +9
Cross-view Referring Multi-Object Tracking (CRMOT) aims to track multiple objects specified by natural language across multiple camera views, with globally consistent identities. D…
Debate-Enhanced Pseudo Labeling and Frequency-Aware Progressive Debiasing for Weakly-Supervised Camouflaged Object Detection with Scribble Annotations
Jiawei Ge, Jiuxin Cao, Xinyi Li +5
Weakly-Supervised Camouflaged Object Detection (WSCOD) aims to locate and segment objects that are visually concealed within their surrounding scenes, relying solely on sparse supe…
Denoise-then-Retrieve: Text-Conditioned Video Denoising for Video Moment Retrieval
Weijia Liu, Jiuxin Cao, Bo Miao +6
Current text-driven Video Moment Retrieval (VMR) methods encode all video clips, including irrelevant ones, disrupting multimodal alignment and hindering optimization. To this end,…
Context-Enhanced Video Moment Retrieval with Large Language Models
Weijia Liu, Bo Miao, Jiuxin Cao +4
Current methods for Video Moment Retrieval (VMR) struggle to align complex situations involving specific environmental details, character descriptions, and action narratives. To ta…
Query-Based Knowledge Sharing for Open-Vocabulary Multi-Label Classification
Xuelin Zhu, Jian Liu, Dongqi Tang +4
Identifying labels that did not appear during training, known as multi-label zero-shot learning, is a non-trivial task in computer vision. To this end, recent studies have attempte…
Text as Image: Learning Transferable Adapter for Multi-Label Classification
Xuelin Zhu, Jiuxin Cao, Jian liu +7
Pre-trained vision-language models have notably accelerated progress of open-world concept recognition. Their impressive zero-shot ability has recently been transferred to multi-la…
Beyond Visual Cues: Synchronously Exploring Target-Centric Semantics for Vision-Language Tracking
Jiawei Ge, Xiangmei Chen, Jiuxin Cao +2
Single object tracking aims to locate one specific target in video sequences, given its initial state. Classical trackers rely solely on visual cues, restricting their ability to h…
Causal-Story: Local Causal Attention Utilizing Parameter-Efficient Tuning For Visual Story Synthesis
Tianyi Song, Jiuxin Cao, Kun Wang +2
The excellent text-to-image synthesis capability of diffusion models has driven progress in synthesizing coherent visual stories. The current state-of-the-art method combines the f…
AlignVE: Visual Entailment Recognition Based on Alignment Relations
Biwei Cao, Jiuxin Cao, Jie Gui +5
Visual entailment (VE) is to recognize whether the semantics of a hypothesis text can be inferred from the given premise image, which is one special task among recent emerged visio…