2 citations · 2 across the 11 of their papers we have counts for
11 papers
VCap: Hypergeometric Rewards for Weak-to-Strong Visual Captioning
Xingyu Lu, Jinpeng Wang, Yi-Fan Zhang +13
Visual captioning requires models to capture visual content faithfully while minimizing both omission and hallucination. As the dominant paradigm for captioning, MLLMs have achieve…
Multi-Camera Self-Calibration in Sports Motion Capture: Leveraging Human and Stick Poses
Fan Yang, Changsoo Jung, Ryosuke Kawamura +1
Multi-camera systems are widely employed in sports to capture the 3D motion of athletes and equipment, yet calibrating their extrinsic parameters remains costly and labor-intensive…
HY-World 2.0: A Multi-Modal World Model for Reconstructing, Generating, and Simulating 3D Worlds
Team HY-World, Chenjie Cao, Xuhui Zuo +42
We introduce HY-World 2.0, a multi-modal world model framework that advances our prior project HY-World 1.0. HY-World 2.0 accommodates diverse input modalities, including text prom…
ViSA: 3D-Aware Video Shading for Real-Time Upper-Body Avatar Creation
Fan Yang, Heyuan Li, Peihao Li +9
Generating high-fidelity upper-body 3D avatars from one-shot input image remains a significant challenge. Current 3D avatar generation methods, which rely on large reconstruction m…
Puppeteer: Rig and Animate Your 3D Models
Chaoyue Song, Xiu Li, Fan Yang +6
Modern interactive applications increasingly demand dynamic 3D content, yet the transformation of static 3D models into animated assets constitutes a significant bottleneck in cont…
MagicArticulate: Make Your 3D Models Articulation-Ready
Chaoyue Song, Jianfeng Zhang, Xiu Li +8
With the explosive growth of 3D content creation, there is an increasing demand for automatically converting static 3D models into articulation-ready versions that support realisti…
Deblur-Avatar: Animatable Avatars from Motion-Blurred Monocular Videos
Xianrui Luo, Juewen Peng, Zhongang Cai +4
We introduce a novel framework for modeling high-fidelity, animatable 3D human avatars from motion-blurred monocular video inputs. Motion blur is prevalent in real-world dynamic vi…
Magic-Boost: Boost 3D Generation with Multi-View Conditioned Diffusion
Fan Yang, Jianfeng Zhang, Yichun Shi +7
Benefiting from the rapid development of 2D diffusion models, 3D content generation has witnessed significant progress. One promising solution is to finetune the pre-trained 2D dif…
Sculpt3D: Multi-View Consistent Text-to-3D Generation with Sparse 3D Prior
Cheng Chen, Xiaofeng Yang, Fan Yang +5
Recent works on text-to-3d generation show that using only 2D diffusion supervision for 3D generation tends to produce results with inconsistent appearances (e.g., faces on the bac…
AttriHuman-3D: Editable 3D Human Avatar Generation with Attribute Decomposition and Indexing
Fan Yang, Tianyi Chen, Xiaosheng He +4
Editable 3D-aware generation, which supports user-interacted editing, has witnessed rapid development recently. However, existing editable 3D GANs either fail to achieve high-accur…
Few-shot Image Generation via Style Adaptation and Content Preservation
Xiaosheng He, Fan Yang, Fayao Liu +1
Training a generative model with limited data (e.g., 10) is a very challenging task. Many works propose to fine-tune a pre-trained GAN model. However, this can easily result in ove…