1 citations · 1 across the 2 of their papers we have counts for
3 papers
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.CV2024★ 1 cited
MCF-VC: Mitigate Catastrophic Forgetting in Class-Incremental Learning for Multimodal Video Captioning
Huiyu Xiong, Lanxiao Wang, Heqian Qiu +3
To address the problem of catastrophic forgetting due to the invisibility of old categories in sequential input, existing work based on relatively simple categorization tasks has m…
cs.CV2023
GRSDet: Learning to Generate Local Reverse Samples for Few-shot Object Detection
Hefei Mei, Taijin Zhao, Shiyuan Tang +5
Few-shot object detection (FSOD) aims to achieve object detection only using a few novel class training data. Most of the existing methods usually adopt a transfer-learning strateg…