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Chao Ding

13 papers hereh-index 9803 citations25 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • first author1
  • middle author12

Across the 13 of 13 papers where every author was matched, so the position is known.

fields
  • cs.CV10
  • cs.HC2
  • eess.IV1
same name
  • Chao Ding — 15 papers, h 11
  • Chao Ding — 7 papers, h 2
  • Chao Ding — 4 papers, h 2
  • Chao Ding — 4 papers, h 5
  • Chao Ding — 4 papers, h 2
  • Chao Ding — 2 papers, h 1

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

activity
20232026
most citedSAM Fails to Segment Anything? -- SAM-Adapter: Adapting SAM in Underperformed Scenes: Camouflage, Shadow, Medical Image Segmentation, and More

41 citations · 58 across the 13 of their papers we have counts for

collaborators
Showing 2026Show all

4 papers · 1 filter

cs.CV2026

MoWorld: A Flash World Model

Team Moxin, Deyi Ji, Tianrun Chen +37

The future of World Models depends not only on scaling model capability, but also on scaling practicality and inference efficiency. High-frame-rate inference enables responsive per…

cs.CV2026

4DVGGT-D: 4D Visual Geometry Transformer with Improved Dynamic Depth Estimation

Ying Zang, Xuanyi Liu, Yidong Han +9

Reconstructing dynamic 4D scenes from monocular videos is a fundamental yet challenging task. While recent 3D foundation models provide strong geometric priors, their performance s…

cs.CV2026

Robust 4D Visual Geometry Transformer with Uncertainty-Aware Priors

Ying Zang, Yidong Han, Chaotao Ding +8

Reconstructing dynamic 4D scenes is an important yet challenging task. While 3D foundation models like VGGT excel in static settings, they often struggle with dynamic sequences whe…

cs.CV2026

HD-VGGT: High-Resolution Visual Geometry Transformer

Tianrun Chen, Yuanqi Hu, Yidong Han +11

High-resolution imagery is essential for accurate 3D reconstruction, as many geometric details only emerge at fine spatial scales. Recent feed-forward approaches, such as the Visua…

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Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.