9 citations · 14 across the 7 of their papers we have counts for
4 papers · 1 filter
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…
Frequency-Aware Self-Supervised Monocular Depth Estimation
Xingyu Chen, Thomas H. Li, Ruonan Zhang +1
We present two versatile methods to generally enhance self-supervised monocular depth estimation (MDE) models. The high generalizability of our methods is achieved by solving the f…
Self-Supervised Monocular Depth Estimation: Solving the Edge-Fattening Problem
Xingyu Chen, Ruonan Zhang, Ji Jiang +3
Self-supervised monocular depth estimation (MDE) models universally suffer from the notorious edge-fattening issue. Triplet loss, as a widespread metric learning strategy, has larg…
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…