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cs.CV2025
Attention-disentangled Uniform Orthogonal Feature Space Optimization for Few-shot Object Detection
Taijin Zhao, Heqian Qiu, Yu Dai +4
Few-shot object detection (FSOD) aims to detect objects with limited samples for novel classes, while relying on abundant data for base classes. Existing FSOD approaches, predomina…
cs.CV2025
Modulating CNN Features with Pre-Trained ViT Representations for Open-Vocabulary Object Detection
Xiangyu Gao, Yu Dai, Benliu Qiu +3
Owing to large-scale image-text contrastive training, pre-trained vision language model (VLM) like CLIP shows superior open-vocabulary recognition ability. Most existing open-vocab…
cs.CV2024
Slightly Shift New Classes to Remember Old Classes for Video Class-Incremental Learning
Jian Jiao, Yu Dai, Hefei Mei +5
Recent video class-incremental learning usually excessively pursues the accuracy of the newly seen classes and relies on memory sets to mitigate catastrophic forgetting of the old…