33 citations · 67 across the 15 of their papers we have counts for
15 papers
Guide3D: Create 3D Avatars from Text and Image Guidance
Yukang Cao, Yan-Pei Cao, Kai Han +2
Recently, text-to-image generation has exhibited remarkable advancements, with the ability to produce visually impressive results. In contrast, text-to-3D generation has not yet re…
GET3D--: Learning GET3D from Unconstrained Image Collections
Fanghua Yu, Xintao Wang, Zheyuan Li +3
The demand for efficient 3D model generation techniques has grown exponentially, as manual creation of 3D models is time-consuming and requires specialized expertise. While generat…
Animate-A-Story: Storytelling with Retrieval-Augmented Video Generation
Yingqing He, Menghan Xia, Haoxin Chen +8
Generating videos for visual storytelling can be a tedious and complex process that typically requires either live-action filming or graphics animation rendering. To bypass these c…
NOFA: NeRF-based One-shot Facial Avatar Reconstruction
Wangbo Yu, Yanbo Fan, Yong Zhang +8
3D facial avatar reconstruction has been a significant research topic in computer graphics and computer vision, where photo-realistic rendering and flexible controls over poses and…
Neural Point-based Volumetric Avatar: Surface-guided Neural Points for Efficient and Photorealistic Volumetric Head Avatar
Cong Wang, Di Kang, Yan-Pei Cao +3
Rendering photorealistic and dynamically moving human heads is crucial for ensuring a pleasant and immersive experience in AR/VR and video conferencing applications. However, exist…
DragonDiffusion: Enabling Drag-style Manipulation on Diffusion Models
Chong Mou, Xintao Wang, Jiechong Song +2
Despite the ability of existing large-scale text-to-image (T2I) models to generate high-quality images from detailed textual descriptions, they often lack the ability to precisely…
InstructP2P: Learning to Edit 3D Point Clouds with Text Instructions
Jiale Xu, Xintao Wang, Yan-Pei Cao +3
Enhancing AI systems to perform tasks following human instructions can significantly boost productivity. In this paper, we present InstructP2P, an end-to-end framework for 3D shape…
SGAT4PASS: Spherical Geometry-Aware Transformer for PAnoramic Semantic Segmentation
Xuewei Li, Tao Wu, Zhongang Qi +3
As an important and challenging problem in computer vision, PAnoramic Semantic Segmentation (PASS) gives complete scene perception based on an ultra-wide angle of view. Usually, pr…
PanoGRF: Generalizable Spherical Radiance Fields for Wide-baseline Panoramas
Zheng Chen, Yan-Pei Cao, Yuan-Chen Guo +3
Achieving an immersive experience enabling users to explore virtual environments with six degrees of freedom (6DoF) is essential for various applications such as virtual reality (V…
HOSNeRF: Dynamic Human-Object-Scene Neural Radiance Fields from a Single Video
Jia-Wei Liu, Yan-Pei Cao, Tianyuan Yang +5
We introduce HOSNeRF, a novel 360° free-viewpoint rendering method that reconstructs neural radiance fields for dynamic human-object-scene from a single monocular in-the-wild video…
MasaCtrl: Tuning-Free Mutual Self-Attention Control for Consistent Image Synthesis and Editing
Mingdeng Cao, Xintao Wang, Zhongang Qi +3
Despite the success in large-scale text-to-image generation and text-conditioned image editing, existing methods still struggle to produce consistent generation and editing results…
Learning Anchor Transformations for 3D Garment Animation
Fang Zhao, Zekun Li, Shaoli Huang +5
This paper proposes an anchor-based deformation model, namely AnchorDEF, to predict 3D garment animation from a body motion sequence. It deforms a garment mesh template by a mixtur…
DreamAvatar: Text-and-Shape Guided 3D Human Avatar Generation via Diffusion Models
Yukang Cao, Yan-Pei Cao, Kai Han +2
We present DreamAvatar, a text-and-shape guided framework for generating high-quality 3D human avatars with controllable poses. While encouraging results have been reported by rece…
VMesh: Hybrid Volume-Mesh Representation for Efficient View Synthesis
Yuan-Chen Guo, Yan-Pei Cao, Chen Wang +4
With the emergence of neural radiance fields (NeRFs), view synthesis quality has reached an unprecedented level. Compared to traditional mesh-based assets, this volumetric represen…
Vis2Mus: Exploring Multimodal Representation Mapping for Controllable Music Generation
Runbang Zhang, Yixiao Zhang, Kai Shao +2
In this study, we explore the representation mapping from the domain of visual arts to the domain of music, with which we can use visual arts as an effective handle to control musi…