5 citations · 7 across the 12 of their papers we have counts for
14 papers
RIGen: Beyond Action Following with Reciprocal Interaction in Generative Gameplay
Mengfei Li, Yi Zhang, Xingtong Ge +8
Generative gameplay requires more than immediate responses to player actions.Actions should have persistent consequences, while the generated world should act according to its own…
PURE: Refining Feed-forward 3D Reconstruction with Unlabeled Post-training
Yaolong Zhu, Peng Li, Jiahao Lu +8
Feed-forward 3D reconstruction models have achieved remarkable progress through large-scale training and strong learned priors. However, they remain fragile when applied to dynamic…
Efficient RWKV-based Representation Learning for 3D Point Clouds
Yun Liu, Xuefeng Yan, Liangliang Nan +5
The recent receptance weighted key value (RWKV) model combines RNN-style recurrence, offering a linear-complexity alternative to Transformers' quadratic self-attention for modeling…
LUNA: Learning Universal 3D Human Animation Beyond Skinning
Peng Li, Rawal Khirodkar, Junxuan Li +6
Creating photorealistic, animatable 3D human avatars from monocular images still largely depends on Linear Blend Skinning (LBS) and parametric body models, which constrain expressi…
Know3D: Prompting 3D Generation with Knowledge from Vision-Language Models
Wenyue Chen, Wenjue Chen, Peng Li +6
Recent advances in 3D generation have improved the fidelity and geometric details of synthesized 3D assets. However, due to the inherent ambiguity of single-view observations and t…
UniSH: Unifying Scene and Human Reconstruction in a Feed-Forward Pass
Mengfei Li, Peng Li, Zheng Zhang +9
We present UniSH, a unified, feed-forward framework for joint metric-scale 3D scene and human reconstruction. A key challenge in this domain is the scarcity of large-scale, annotat…
SyncHuman: Synchronizing 2D and 3D Generative Models for Single-view Human Reconstruction
Wenyue Chen, Peng Li, Wangguandong Zheng +6
Photorealistic 3D full-body human reconstruction from a single image is a critical yet challenging task for applications in films and video games due to inherent ambiguities and se…
PanoLAM: Large Avatar Model for Gaussian Full-Head Synthesis from One-shot Unposed Image
Peng Li, Yisheng He, Yingdong Hu +8
We present a feed-forward framework for static Gaussian full-head reconstruction and novel-view rendering from a single unposed image. Unlike previous work that relies on time-cons…
CMD: Controllable Multiview Diffusion for 3D Editing and Progressive Generation
Peng Li, Suizhi Ma, Jialiang Chen +7
Recently, 3D generation methods have shown their powerful ability to automate 3D model creation. However, most 3D generation methods only rely on an input image or a text prompt to…
PSHuman: Photorealistic Single-image 3D Human Reconstruction using Cross-Scale Multiview Diffusion and Explicit Remeshing
Peng Li, Wangguandong Zheng, Yuan Liu +9
Detailed and photorealistic 3D human modeling is essential for various applications and has seen tremendous progress. However, full-body reconstruction from a monocular RGB image r…
Multi-View Large Reconstruction Model via Geometry-Aware Positional Encoding and Attention
Mengfei Li, Xiaoxiao Long, Yixun Liang +6
Despite recent advancements in the Large Reconstruction Model (LRM) demonstrating impressive results, when extending its input from single image to multiple images, it exhibits ine…
CoCoGesture: Toward Coherent Co-speech 3D Gesture Generation in the Wild
Xingqun Qi, Hengyuan Zhang, Yatian Wang +10
Deriving co-speech 3D gestures has seen tremendous progress in virtual avatar animation. Yet, the existing methods often produce stiff and unreasonable gestures with unseen human s…
Era3D: High-Resolution Multiview Diffusion using Efficient Row-wise Attention
Peng Li, Yuan Liu, Xiaoxiao Long +10
In this paper, we introduce Era3D, a novel multiview diffusion method that generates high-resolution multiview images from a single-view image. Despite significant advancements in…
Weakly-Supervised Emotion Transition Learning for Diverse 3D Co-speech Gesture Generation
Xingqun Qi, Jiahao Pan, Peng Li +8
Generating vivid and emotional 3D co-speech gestures is crucial for virtual avatar animation in human-machine interaction applications. While the existing methods enable generating…