Haoye Dong

CLIP-GS: Unifying Vision-Language Representation with 3D Gaussian Splatting

Siyu Jiao, Haoye Dong, Yuyang Yin, Zequn Jie et autres

Recent works in 3D multimodal learning have made remarkable progress. However, typically 3D multimodal models are only capable of handling point clouds. Compared to the emerging 3D representation technique, 3D Gaussian Splatting (3DGS), the spatially sparse point cloud cannot depict the texture …

cn, sg, us (code pays fourni par la source)

PS-Mamba: Spatial-Temporal Graph Mamba for Pose Sequence Refinement

Haoye Dong, G Y Lee

sg (code pays fourni par la source)

Disentangling Multiplex Spatial-Temporal Transition Graph Representation Learning for Socially Enhanced POI Recommendation

Jie Li, Haoye Dong, Zhengyang Wu, Zetao Zheng et autres

Next Point-of-Interest (POI) recommendation is a research hotspot in business intelligence, where users' spatial-temporal transitions and social relationships play key roles. However, most existing works model spatial and temporal transitions separately, leading to misaligned representations of the same spatial-temporal key nodes. This …

Learnable Infinite Taylor Gaussian for Dynamic View Rendering

Bingbing Hu, Yanyan Li, Rui Zhen Xie, Bo Xu et autres

Capturing the temporal evolution of Gaussian properties such as position, rotation, and scale is a challenging task due to the vast number of time-varying parameters and the limited photometric data available, which generally results in convergence issues, making it difficult to find …

cn, sg (code pays fourni par la source)

MV-SSM: Multi-View State Space Modeling for 3D Human Pose Estimation

Aviral Chharia, Wenbo Gou, Haoye Dong

While significant progress has been made in single-view 3D human pose estimation, multi-view 3D human pose estimation remains challenging, particularly in terms of generalizing to new camera configurations. Existing attention-based transformers often struggle to accurately model the spatial arrangement of keypoints, especially …

us, sg (code pays fourni par la source)

Learnable Infinite Taylor Gaussian for Dynamic View Rendering

Bingbing Hu, Yanyan Li, Rui Zhen Xie, Bo Xu et autres

Capturing the temporal evolution of Gaussian properties such as position, rotation, and scale is a challenging task due to the vast number of time-varying parameters and the limited photometric data available, which generally results in convergence issues, making it difficult to find …

DreamVTON: Customizing 3D Virtual Try-on with Personalized Diffusion Models

Zhenyu Xie, Haoye Dong, Xiaodan Liang

cn, us (code pays fourni par la source)

Generalizable Human Gaussians for Sparse View Synthesis

Youngjoong Kwon, Baole Fang, Yixing Lu, Haoye Dong et autres

us (code pays fourni par la source)

Human-VDM: Learning Single-Image 3D Human Gaussian Splatting from Video Diffusion Models

Zhibin Liu, Haoye Dong, Aviral Chharia, Hefeng Wu

Generating lifelike 3D humans from a single RGB image remains a challenging task in computer vision, as it requires accurate modeling of geometry, high-quality texture, and plausible unseen parts. Existing methods typically use multi-view diffusion models for 3D generation, but they often …

DreamVTON: Customizing 3D Virtual Try-on with Personalized Diffusion Models

Zhenyu Xie, Haoye Dong, Zhengwu Ma, Xiaodan Liang

Image-based 3D Virtual Try-ON (VTON) aims to sculpt the 3D human according to person and clothes images, which is data-efficient (i.e., getting rid of expensive 3D data) but challenging. Recent text-to-3D methods achieve remarkable improvement in high-fidelity 3D human generation, demonstrating its …

Generalizable Human Gaussians for Sparse View Synthesis

Youngjoong Kwon, Baole Fang, Yixing Lu, Haoye Dong et autres

Recent progress in neural rendering has brought forth pioneering methods, such as NeRF and Gaussian Splatting, which revolutionize view rendering across various domains like AR/VR, gaming, and content creation. While these methods excel at interpolating {\em within the training data}, the challenge …

Hamba: Single-view 3D Hand Reconstruction with Graph-guided Bi-Scanning Mamba

Haoye Dong, Aviral Chharia, Wenbo Gou, Francisco Vicente Carrasco et autres

3D Hand reconstruction from a single RGB image is challenging due to the articulated motion, self-occlusion, and interaction with objects. Existing SOTA methods employ attention-based transformers to learn the 3D hand pose and shape, yet they do not fully achieve robust and …