activity
20222024
most citedFrom Semi-supervised to Omni-supervised Room Layout Estimation Using Point Clouds

2 citations · 4 across the 7 of their papers we have counts for

collaborators

7 papers

cs.CV2024

Training-Free Model Merging for Multi-target Domain Adaptation

Wenyi Li, Huan-ang Gao, Mingju Gao +3

In this paper, we study multi-target domain adaptation of scene understanding models. While previous methods achieved commendable results through inter-domain consistency losses, t…

cs.CV20241 cited

Adaptive Surface Normal Constraint for Geometric Estimation from Monocular Images

Xiaoxiao Long, Yuhang Zheng, Yupeng Zheng +6

We introduce a novel approach to learn geometries such as depth and surface normal from images while incorporating geometric context. The difficulty of reliably capturing geometric…

cs.CV2024

Key Patch Proposer: Key Patches Contain Rich Information

Jing Xu, Beiwen Tian, Hao Zhao

In this paper, we introduce a novel algorithm named Key Patch Proposer (KPP) designed to select key patches in an image without additional training. Our experiments showcase KPP's…

cs.CV20241 cited

Latency-aware Road Anomaly Segmentation in Videos: A Photorealistic Dataset and New Metrics

Beiwen Tian, Huan-ang Gao, Leiyao Cui +6

In the past several years, road anomaly segmentation is actively explored in the academia and drawing growing attention in the industry. The rationale behind is straightforward: if…

cs.CV2023

Delving into Shape-aware Zero-shot Semantic Segmentation

Xinyu Liu, Beiwen Tian, Zhen Wang +5

Thanks to the impressive progress of large-scale vision-language pretraining, recent recognition models can classify arbitrary objects in a zero-shot and open-set manner, with a su…

cs.CV20232 cited

From Semi-supervised to Omni-supervised Room Layout Estimation Using Point Clouds

Huan-ang Gao, Beiwen Tian, Pengfei Li +5

Room layout estimation is a long-existing robotic vision task that benefits both environment sensing and motion planning. However, layout estimation using point clouds (PCs) still…