2 citations · 4 across the 8 of their papers we have counts for
9 papers
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…
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…
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…
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…
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…
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…
Lotus: Diffusion-based Visual Foundation Model for High-quality Dense Prediction
Jing He, Haodong Li, Wei Yin +6
Leveraging the visual priors of pre-trained text-to-image diffusion models offers a promising solution to enhance zero-shot generalization in dense prediction tasks. However, exist…
RADA: Robust and Accurate Feature Learning with Domain Adaptation
Jingtai He, Gehao Zhang, Tingting Liu +1
Recent advancements in keypoint detection and descriptor extraction have shown impressive performance in local feature learning tasks. However, existing methods generally exhibit s…
Traffic Video Object Detection using Motion Prior
Lihao Liu, Yanqi Cheng, Dongdong Chen +4
Traffic videos inherently differ from generic videos in their stationary camera setup, thus providing a strong motion prior where objects often move in a specific direction over a…