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Dual-Adapter: Training-free Dual Adaptation for Few-shot Out-of-Distribution Detection
Xinyi Chen, Yaohui Li, Haoxing Chen
We study the problem of few-shot out-of-distribution (OOD) detection, which aims to detect OOD samples from unseen categories during inference time with only a few labeled in-domai…
DeMamba: AI-Generated Video Detection on Million-Scale GenVideo Benchmark
Haoxing Chen, Yan Hong, Zizheng Huang +8
Recently, video generation techniques have advanced rapidly. Given the popularity of video content on social media platforms, these models intensify concerns about the spread of fa…
The Devil is in the Few Shots: Iterative Visual Knowledge Completion for Few-shot Learning
Yaohui Li, Qifeng Zhou, Haoxing Chen +3
Contrastive Language-Image Pre-training (CLIP) has shown powerful zero-shot learning performance. Few-shot learning aims to further enhance the transfer capability of CLIP by givin…
Conditional Prototype Rectification Prompt Learning
Haoxing Chen, Yaohui Li, Zizheng Huang +6
Pre-trained large-scale vision-language models (VLMs) have acquired profound understanding of general visual concepts. Recent advancements in efficient transfer learning (ETL) have…
Segment Anything Model Meets Image Harmonization
Haoxing Chen, Yaohui Li, Zhangxuan Gu +3
Image harmonization is a crucial technique in image composition that aims to seamlessly match the background by adjusting the foreground of composite images. Current methods adopt…
Boosting Audio-visual Zero-shot Learning with Large Language Models
Haoxing Chen, Yaohui Li, Yan Hong +6
Audio-visual zero-shot learning aims to recognize unseen classes based on paired audio-visual sequences. Recent methods mainly focus on learning multi-modal features aligned with c…