203 citations · 293 across the 13 of their papers we have counts for
6 papers · 1 filter
LINK: Adaptive Modality Interaction for Audio-Visual Video Parsing
Langyu Wang, Bingke Zhu, Yingying Chen +1
Audio-visual video parsing focuses on classifying videos through weak labels while identifying events as either visible, audible, or both, alongside their respective temporal bound…
UniVAD: A Training-free Unified Model for Few-shot Visual Anomaly Detection
Zhaopeng Gu, Bingke Zhu, Guibo Zhu +3
Visual Anomaly Detection (VAD) aims to identify abnormal samples in images that deviate from normal patterns, covering multiple domains, including industrial, logical, and medical…
Friend or Foe? Harnessing Controllable Overfitting for Anomaly Detection
Long Qian, Bingke Zhu, Yingying Chen +2
Overfitting has traditionally been viewed as detrimental to anomaly detection, where excessive generalization often limits models' sensitivity to subtle anomalies. Our work challen…
The BRAVO Semantic Segmentation Challenge Results in UNCV2024
Tuan-Hung Vu, Eduardo Valle, Andrei Bursuc +16
We propose the unified BRAVO challenge to benchmark the reliability of semantic segmentation models under realistic perturbations and unknown out-of-distribution (OOD) scenarios. W…
MROVSeg: Breaking the Resolution Curse of Vision-Language Models in Open-Vocabulary Image Segmentation
Yuanbing Zhu, Bingke Zhu, Yingying Chen +3
Pretrained vision-language models (VLMs), \eg CLIP, are increasingly used to bridge the gap between open- and close-vocabulary recognition in open-vocabulary image segmentation. As…
Optimization of Prompt Learning via Multi-Knowledge Representation for Vision-Language Models
Enming Zhang, Bingke Zhu, Yingying Chen +3
Vision-Language Models (VLMs), such as CLIP, play a foundational role in various cross-modal applications. To fully leverage VLMs' potential in adapting to downstream tasks, contex…