7 papers
StableVLA: Towards Robust Vision-Language-Action Models without Extra Data
Yiyang Fu, Chubin Zhang, Shukai Gong +7
It is infeasible to encompass all possible disturbances within the training dataset. This raises a critical question regarding the robustness of Vision-Language-Action (VLA) models…
TaskGround: Structured Executable Task Inference for Full-Scene Household Reasoning
ZhiYuan Feng, Yu Deng, Ruichuan An +11
In real home deployments, household agents must often operate from a complete household scene and a situated household request, rather than from a clean task specification. Such re…
Native and Compact Structured Latents for 3D Generation
Jianfeng Xiang, Xiaoxue Chen, Sicheng Xu +8
Recent advancements in 3D generative modeling have significantly improved the generation realism, yet the field is still hampered by existing representations, which struggle to cap…
MoGe-2: Accurate Monocular Geometry with Metric Scale and Sharp Details
Ruicheng Wang, Sicheng Xu, Yue Dong +6
We propose MoGe-2, an advanced open-domain geometry estimation model that recovers a metric scale 3D point map of a scene from a single image. Our method builds upon the recent mon…
Structured 3D Latents for Scalable and Versatile 3D Generation
Jianfeng Xiang, Zelong Lv, Sicheng Xu +6
We introduce a novel 3D generation method for versatile and high-quality 3D asset creation. The cornerstone is a unified Structured LATent (SLAT) representation which allows decodi…
MoGe: Unlocking Accurate Monocular Geometry Estimation for Open-Domain Images with Optimal Training Supervision
Ruicheng Wang, Sicheng Xu, Cassie Dai +4
We present MoGe, a powerful model for recovering 3D geometry from monocular open-domain images. Given a single image, our model directly predicts a 3D point map of the captured sce…