3 papers
cs.CV2024
HUWSOD: Holistic Self-training for Unified Weakly Supervised Object Detection
Liujuan Cao, Jianghang Lin, Zebo Hong +4
Most WSOD methods rely on traditional object proposals to generate candidate regions and are confronted with unstable training, which easily gets stuck in a poor local optimum. In…
cs.CV2022
FoPro: Few-Shot Guided Robust Webly-Supervised Prototypical Learning
Yulei Qin, Xingyu Chen, Chao Chen +5
Recently, webly supervised learning (WSL) has been studied to leverage numerous and accessible data from the Internet. Most existing methods focus on learning noise-robust models f…
cs.CV2022
ECO-TR: Efficient Correspondences Finding Via Coarse-to-Fine Refinement
Dongli Tan, Jiang-Jiang Liu, Xingyu Chen +5
Modeling sparse and dense image matching within a unified functional correspondence model has recently attracted increasing research interest. However, existing efforts mainly focu…