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Shen Cao

5 accepted papers

2026

TrackGS: Optimizing COLMAP-Free 3D Gaussian Splatting with Global Track Constraints

AAAI 2026technical

We present TrackGS, a novel method to integrate global feature tracks with 3D Gaussian Splatting (3DGS) for COLMAP-free novel view synthesis. While 3DGS delivers impressive rendering quality, its reliance on accurate precomputed camera parameters remains a significant limitation. Existing COLMAP-fre

Cited by 0SourcePDFScholar
2025

CoL3D: Collaborative Learning of Single-view Depth and Camera Intrinsics for Metric 3D Shape Recovery

ICRA 2025

Recovering the metric 3D shape from a single image is particularly relevant for robotics and embodied in-telligence applications, where accurate spatial understanding is crucial for navigation and interaction with environments. Usu-ally, the mainstream approaches achieve it through monocular depth e

Cited by 0SourceScholar
2025

SD-VLM: Spatial Measuring and Understanding with Depth-Encoded Vision-Language Models

NeurIPS 2025poster

While vision language models (VLMs) excel in 2D semantic visual understanding, their ability to quantitatively reason about 3D spatial relationships remains underexplored due to the deficiency of spatial representation ability of 2D images. In this paper, we analyze the problem hindering VLMs’ spat…

Cited by 0SourcecodeScholar
2022

Homography Loss for Monocular 3D Object Detection

CVPR 2022poster

Monocular 3D object detection is an essential task in autonomous driving. However, most current methods consider each 3D object in the scene as an independent training sample, while ignoring their inherent geometric relations, thus inevitably resulting in a lack of leveraging spatial constraints. In…

Cited by 59PDFcodeScholar