40 citations · 206 across the 27 of their papers we have counts for
4 papers · 1 filter
Camera Pose Matters: Improving Depth Prediction by Mitigating Pose Distribution Bias
Yunhan Zhao, Shu Kong, Charless Fowlkes
Monocular depth predictors are typically trained on large-scale training sets which are naturally biased w.r.t the distribution of camera poses. As a result, trained predictors fai…
Weak Supervision and Referring Attention for Temporal-Textual Association Learning
Zhiyuan Fang, Shu Kong, Zhe Wang +2
A system capturing the association between video frames and textual queries offer great potential for better video analysis. However, training such a system in a fully supervised w…
Celeganser: Automated Analysis of Nematode Morphology and Age
Linfeng Wang, Shu Kong, Zachary Pincus +1
The nematode Caenorhabditis elegans (C. elegans) serves as an important model organism in a wide variety of biological studies. In this paper we introduce a pipeline for automated…
Domain Decluttering: Simplifying Images to Mitigate Synthetic-Real Domain Shift and Improve Depth Estimation
Yunhan Zhao, Shu Kong, Daeyun Shin +1
Leveraging synthetically rendered data offers great potential to improve monocular depth estimation and other geometric estimation tasks, but closing the synthetic-real domain gap…