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

2 citations · 3 across the 7 of their papers we have counts for

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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

DA: Depth Anything in Any Direction

Haodong Li, Wangguangdong Zheng, Jing He +5

Panorama has a full FoV (360180), 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…

cs.CV2024

DisEnvisioner: Disentangled and Enriched Visual Prompt for Customized Image Generation

Jing He, Haodong Li, Yongzhe Hu +4

In the realm of image generation, creating customized images from visual prompt with additional textual instruction emerges as a promising endeavor. However, existing methods, both…

cs.CV2024

OmniBooth: Learning Latent Control for Image Synthesis with Multi-modal Instruction

Leheng Li, Weichao Qiu, Xu Yan +6

We present OmniBooth, an image generation framework that enables spatial control with instance-level multi-modal customization. For all instances, the multimodal instruction can be…