50 citations · 196 across the 45 of their papers we have counts for
9 papers · 1 filter
Revisiting Foreground and Background Separation in Weakly-supervised Temporal Action Localization: A Clustering-based Approach
Qinying Liu, Zilei Wang, Shenghai Rong +2
Weakly-supervised temporal action localization aims to localize action instances in videos with only video-level action labels. Existing methods mainly embrace a localization-by-cl…
TagAlign: Improving Vision-Language Alignment with Multi-Tag Classification
Qinying Liu, Wei Wu, Kecheng Zheng +6
The crux of learning vision-language models is to extract semantically aligned information from visual and linguistic data. Existing attempts usually face the problem of coarse ali…
Exploiting Low-confidence Pseudo-labels for Source-free Object Detection
Zhihong Chen, Zilei Wang, Yixin Zhang
Source-free object detection (SFOD) aims to adapt a source-trained detector to an unlabeled target domain without access to the labeled source data. Current SFOD methods utilize a…
Improving Zero-Shot Generalization for CLIP with Synthesized Prompts
Zhengbo Wang, Jian Liang, Ran He +3
With the growing interest in pretrained vision-language models like CLIP, recent research has focused on adapting these models to downstream tasks. Despite achieving promising resu…
SimpleNet: A Simple Network for Image Anomaly Detection and Localization
Zhikang Liu, Yiming Zhou, Yuansheng Xu +1
We propose a simple and application-friendly network (called SimpleNet) for detecting and localizing anomalies. SimpleNet consists of four components: (1) a pre-trained Feature Ext…
Semantic Prompt for Few-Shot Image Recognition
Wentao Chen, Chenyang Si, Zhang Zhang +3
Few-shot learning is a challenging problem since only a few examples are provided to recognize a new class. Several recent studies exploit additional semantic information, e.g. tex…
Exploiting Semantic Attributes for Transductive Zero-Shot Learning
Zhengbo Wang, Jian Liang, Zilei Wang +1
Zero-shot learning (ZSL) aims to recognize unseen classes by generalizing the relation between visual features and semantic attributes learned from the seen classes. A recent parad…
AdaptGuard: Defending Against Universal Attacks for Model Adaptation
Lijun Sheng, Jian Liang, Ran He +2
Model adaptation aims at solving the domain transfer problem under the constraint of only accessing the pretrained source models. With the increasing considerations of data privacy…
Video Semantic Segmentation with Inter-Frame Feature Fusion and Inner-Frame Feature Refinement
Jiafan Zhuang, Zilei Wang, Junjie Li
Video semantic segmentation aims to generate accurate semantic maps for each video frame. To this end, many works dedicate to integrate diverse information from consecutive frames…