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Jing He

9 papers hereh-index 5222 citations9 works total

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

author position
  • first author4
  • middle author5

Across the 9 of 9 papers where every author was matched, so the position is known.

fields
  • cs.CV9
same name
  • Jing He — 23 papers, h 8
  • Jing He — 16 papers, h 3
  • Jing He — 6 papers, h 5
  • Jing He — 5 papers, h 1
  • Jing He — 3 papers, h 4
  • Jing He — 3 papers, h 3

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
20232025
most citedLotus: Diffusion-based Visual Foundation Model for High-quality Dense Prediction

2 citations · 4 across the 8 of their papers we have counts for

collaborators
Showing 2025Show all

4 papers · 1 filter

cs.CV2025

Lotus-2: Advancing Geometric Dense Prediction with Powerful Image Generative Model

Jing He, Haodong Li, Mingzhi Sheng +1

Recovering pixel-wise geometric properties from a single image is fundamentally ill-posed due to appearance ambiguity and non-injective mappings between 2D observations and 3D stru…

cs.CV2025

DA2: Depth Anything in Any Direction

Haodong Li, Wangguangdong Zheng, Jing He +5

Panorama has a full FoV (360∘×180∘), offering a more complete visual description than perspective images. Thanks to this characteristic, panoramic depth estimati…

cs.CV2025

SDPose: Exploiting Diffusion Priors for Out-of-Domain and Robust Pose Estimation

Shuang Liang, Jing He, Chuanmeizhi Wang +4

Pre-trained diffusion models provide rich latent features across U-Net levels and are emerging as powerful vision backbones. While prior works such as Marigold and Lotus repurpose…

cs.CV2025

Jasmine: Harnessing Diffusion Prior for Self-supervised Depth Estimation

Jiyuan Wang, Chunyu Lin, Cheng Guan +5

In this paper, we propose Jasmine, the first Stable Diffusion (SD)-based self-supervised framework for monocular depth estimation, which effectively harnesses SD's visual priors to…

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