5 citations · 7 across the 12 of their papers we have counts for
6 papers · 1 filter
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…