activity
20152026
most citedLSUN: Construction of a Large-scale Image Dataset using Deep Learning with Humans in the Loop

1.3k citations · 2.6k across the 63 of their papers we have counts for

collaborators

65 papers

cs.CV2026

MFlowHOI: Whole-Body Human-Object Interaction Generation via Part-Aware MeanFlow

Qiang He, Yonghao Zhang, Yinda Zhang +7

Whole-body human-object interaction (HOI) generation requires coordinating body and finger motion, object trajectories, and time-varying contacts. Existing methods typically rely o…

cs.CV2026

Archon: A Unified Multimodal Model for Holistic Digital Human Generation

Chong Bao, Shichen Liu, Lijun Yu +9

Digital humans are fundamental to immersive interaction, yet creating a unified model for holistic modalities, including text, audio, motion, and visual content, remains an open ch…

cs.CV2026

EgoRelight: Egocentric Human Capture and Illumination Recovery for Relightable and Photoreal Avatar Rendering

Jianchun Chen, Yinda Zhang, Rohit Pandey +3

Mixed Reality (MR) headsets promise a future of immersive telepresence where virtual humans blend indistinguishably into real or virtual surroundings. Achieving this vision require…

cs.CV2025

S^2VG: 3D Stereoscopic and Spatial Video Generation via Denoising Frame Matrix

Peng Dai, Feitong Tan, Qiangeng Xu +6

While video generation models excel at producing high-quality monocular videos, generating 3D stereoscopic and spatial videos for immersive applications remains an underexplored ch…

cs.CV2025

HOGSA: Bimanual Hand-Object Interaction Understanding with 3D Gaussian Splatting Based Data Augmentation

Wentian Qu, Jiahe Li, Jian Cheng +6

Understanding of bimanual hand-object interaction plays an important role in robotics and virtual reality. However, due to significant occlusions between hands and object as well a…

cs.CV2024

SVG: 3D Stereoscopic Video Generation via Denoising Frame Matrix

Peng Dai, Feitong Tan, Qiangeng Xu +5

Video generation models have demonstrated great capabilities of producing impressive monocular videos, however, the generation of 3D stereoscopic video remains under-explored. We p…

cs.CV2024★ 15 cited

GaussianPrediction: Dynamic 3D Gaussian Prediction for Motion Extrapolation and Free View Synthesis

Boming Zhao, Yuan Li, Ziyu Sun +6

Forecasting future scenarios in dynamic environments is essential for intelligent decision-making and navigation, a challenge yet to be fully realized in computer vision and roboti…

cs.CV2024

GeneAvatar: Generic Expression-Aware Volumetric Head Avatar Editing from a Single Image

Chong Bao, Yinda Zhang, Yuan Li +6

Recently, we have witnessed the explosive growth of various volumetric representations in modeling animatable head avatars. However, due to the diversity of frameworks, there is no…

cs.CV2024

Efficient 3D Implicit Head Avatar with Mesh-anchored Hash Table Blendshapes

Ziqian Bai, Feitong Tan, Sean Fanello +5

3D head avatars built with neural implicit volumetric representations have achieved unprecedented levels of photorealism. However, the computational cost of these methods remains a…

cs.CV2024

CHOSEN: Contrastive Hypothesis Selection for Multi-View Depth Refinement

Di Qiu, Yinda Zhang, Thabo Beeler +5

We propose CHOSEN, a simple yet flexible, robust and effective multi-view depth refinement framework. It can be employed in any existing multi-view stereo pipeline, with straightfo…

cs.CV2024

Pushing Auto-regressive Models for 3D Shape Generation at Capacity and Scalability

Xuelin Qian, Yu Wang, Simian Luo +9

Auto-regressive models have achieved impressive results in 2D image generation by modeling joint distributions in grid space. In this paper, we extend auto-regressive models to 3D…

cs.CV2024

One2Avatar: Generative Implicit Head Avatar For Few-shot User Adaptation

Zhixuan Yu, Ziqian Bai, Abhimitra Meka +6

Traditional methods for constructing high-quality, personalized head avatars from monocular videos demand extensive face captures and training time, posing a significant challenge…

cs.CV2024★ 1 cited

GO-NeRF: Generating Objects in Neural Radiance Fields for Virtual Reality Content Creation

Peng Dai, Feitong Tan, Xin Yu +3

Virtual environments (VEs) are pivotal for virtual, augmented, and mixed reality systems. Despite advances in 3D generation and reconstruction, the direct creation of 3D objects wi…

cs.CV2023

MVDD: Multi-View Depth Diffusion Models

Zhen Wang, Qiangeng Xu, Feitong Tan +6

Denoising diffusion models have demonstrated outstanding results in 2D image generation, yet it remains a challenge to replicate its success in 3D shape generation. In this paper,…

cs.CV2023★ 1 cited

Gaussian3Diff: 3D Gaussian Diffusion for 3D Full Head Synthesis and Editing

Yushi Lan, Feitong Tan, Di Qiu +8

We present a novel framework for generating photorealistic 3D human head and subsequently manipulating and reposing them with remarkable flexibility. The proposed approach leverage…

cs.HC2023★ 8 cited

InstructPipe: Generating Visual Blocks Pipelines with Human Instructions and LLMs

Zhongyi Zhou, Jing Jin, Vrushank Phadnis +16

Visual programming has the potential of providing novice programmers with a low-code experience to build customized processing pipelines. Existing systems typically require users t…

cs.CV2023★ 1 cited

Multi-Modal Neural Radiance Field for Monocular Dense SLAM with a Light-Weight ToF Sensor

Xinyang Liu, Yijin Li, Yanbin Teng +4

Light-weight time-of-flight (ToF) depth sensors are compact and cost-efficient, and thus widely used on mobile devices for tasks such as autofocus and obstacle detection. However,…

cs.CV2023★ 1 cited

Novel-view Synthesis and Pose Estimation for Hand-Object Interaction from Sparse Views

Wentian Qu, Zhaopeng Cui, Yinda Zhang +4

Hand-object interaction understanding and the barely addressed novel view synthesis are highly desired in the immersive communication, whereas it is challenging due to the high def…

cs.CV2023★ 6 cited

Spectral Graphormer: Spectral Graph-based Transformer for Egocentric Two-Hand Reconstruction using Multi-View Color Images

Tze Ho Elden Tse, Franziska Mueller, Zhengyang Shen +8

We propose a novel transformer-based framework that reconstructs two high fidelity hands from multi-view RGB images. Unlike existing hand pose estimation methods, where one typical…

cs.CV2023

Self-supervised Learning of Implicit Shape Representation with Dense Correspondence for Deformable Objects

Baowen Zhang, Jiahe Li, Xiaoming Deng +3

Learning 3D shape representation with dense correspondence for deformable objects is a fundamental problem in computer vision. Existing approaches often need additional annotations…

cs.CV2023★ 9 cited

Grad-PU: Arbitrary-Scale Point Cloud Upsampling via Gradient Descent with Learned Distance Functions

Yun He, Danhang Tang, Yinda Zhang +2

Most existing point cloud upsampling methods have roughly three steps: feature extraction, feature expansion and 3D coordinate prediction. However,they usually suffer from two crit…

cs.CV2023★ 1 cited

Learning Personalized High Quality Volumetric Head Avatars from Monocular RGB Videos

Ziqian Bai, Feitong Tan, Zeng Huang +12

We propose a method to learn a high-quality implicit 3D head avatar from a monocular RGB video captured in the wild. The learnt avatar is driven by a parametric face model to achie…

cs.CV2023

Hybrid Neural Rendering for Large-Scale Scenes with Motion Blur

Peng Dai, Yinda Zhang, Xin Yu +2

Rendering novel view images is highly desirable for many applications. Despite recent progress, it remains challenging to render high-fidelity and view-consistent novel views of la…

cs.CV2023

Learning Versatile 3D Shape Generation with Improved AR Models

Simian Luo, Xuelin Qian, Yanwei Fu +5

Auto-Regressive (AR) models have achieved impressive results in 2D image generation by modeling joint distributions in the grid space. While this approach has been extended to the…