22 citations · 27 across the 22 of their papers we have counts for
9 papers · 1 filter
Filter or Compensate: Towards Invariant Representation from Distribution Shift for Anomaly Detection
Zining Chen, Xingshuang Luo, Weiqiu Wang +3
Recent Anomaly Detection (AD) methods have achieved great success with In-Distribution (ID) data. However, real-world data often exhibits distribution shift, causing huge performan…
UFO: Enhancing Diffusion-Based Video Generation with a Uniform Frame Organizer
Delong Liu, Zhaohui Hou, Mingjie Zhan +3
Recently, diffusion-based video generation models have achieved significant success. However, existing models often suffer from issues like weak consistency and declining image qua…
Modality and Task Adaptation for Enhanced Zero-shot Composed Image Retrieval
Haiwen Li, Fei Su, Zhicheng Zhao
As a challenging vision-language task, Zero-Shot Composed Image Retrieval (ZS-CIR) is designed to retrieve target images using bi-modal (image+text) queries. Typical ZS-CIR methods…
Hierarchical IoU Tracking based on Interval
Yunhao Du, Zhicheng Zhao, Fei Su
Multi-Object Tracking (MOT) aims to detect and associate all targets of given classes across frames. Current dominant solutions, e.g. ByteTrack and StrongSORT++, follow the hybrid…
MindShot: A Few-Shot Brain Decoding Framework via Transferring Cross-Subject Prior and Distilling Frequency Domain Knowledge
Shuai Jiang, Zhu Meng, Haiwen Li +3
Aiming to reconstruct visual stimuli from brain signals, brain decoding has recently made significant progress using functional magnetic resonance imaging (fMRI). However, it still…
Bring Adaptive Binding Prototypes to Generalized Referring Expression Segmentation
Weize Li, Zhicheng Zhao, Haochen Bai +1
Referring Expression Segmentation (RES) has attracted rising attention, aiming to identify and segment objects based on natural language expressions. While substantial progress has…
MLS-Track: Multilevel Semantic Interaction in RMOT
Zeliang Ma, Song Yang, Zhe Cui +4
The new trend in multi-object tracking task is to track objects of interest using natural language. However, the scarcity of paired prompt-instance data hinders its progress. To ad…
PracticalDG: Perturbation Distillation on Vision-Language Models for Hybrid Domain Generalization
Zining Chen, Weiqiu Wang, Zhicheng Zhao +3
Domain Generalization (DG) aims to resolve distribution shifts between source and target domains, and current DG methods are default to the setting that data from source and target…
YYDS: Visible-Infrared Person Re-Identification with Coarse Descriptions
Yunhao Du, Zhicheng Zhao, Fei Su
Visible-infrared person re-identification (VI-ReID) is challenging due to considerable cross-modality discrepancies. Existing works mainly focus on learning modality-invariant feat…