2 citations · 5 across the 3 of their papers we have counts for
3 papers
cs.CV2023★ 1 cited
Uncertainty-Aware Distillation for Semi-Supervised Few-Shot Class-Incremental Learning
Yawen Cui, Wanxia Deng, Haoyu Chen +1
Given a model well-trained with a large-scale base dataset, Few-Shot Class-Incremental Learning (FSCIL) aims at incrementally learning novel classes from a few labeled samples by a…
cs.CV2022★ 2 cited
CD-FSOD: A Benchmark for Cross-domain Few-shot Object Detection
Wuti Xiong
In this paper, we propose a study of the cross-domain few-shot object detection (CD-FSOD) benchmark, consisting of image data from a diverse data domain. On the proposed benchmark,…
cs.CV2020★ 2 cited
Temporal Self-Ensembling Teacher for Semi-Supervised Object Detection
Cong Chen, Shouyang Dong, Ye Tian +3
This paper focuses on Semi-Supervised Object Detection (SSOD). Knowledge Distillation (KD) has been widely used for semi-supervised image classification. However, adapting these me…