38 citations · 95 across the 13 of their papers we have counts for
14 papers
OctWorld: Long-Range World-Consistent Video Generation with Octree-Based 3D Mapping
Zelong Lv, Sicheng Xu, Jianfeng Xiang +5
We present OctWorld, a video diffusion framework with persistent 3D memory for generating explorable, world-consistent, and high-fidelity visual scenes. Given a single image, OctWo…
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…
CogACT: A Foundational Vision-Language-Action Model for Synergizing Cognition and Action in Robotic Manipulation
Qixiu Li, Yaobo Liang, Zeyu Wang +15
The advancement of large Vision-Language-Action (VLA) models has significantly improved robotic manipulation in terms of language-guided task execution and generalization to unseen…
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…
AniFaceGAN: Animatable 3D-Aware Face Image Generation for Video Avatars
Yue Wu, Yu Deng, Jiaolong Yang +3
Although 2D generative models have made great progress in face image generation and animation, they often suffer from undesirable artifacts such as 3D inconsistency when rendering…
Generative Deformable Radiance Fields for Disentangled Image Synthesis of Topology-Varying Objects
Ziyu Wang, Yu Deng, Jiaolong Yang +2
3D-aware generative models have demonstrated their superb performance to generate 3D neural radiance fields (NeRF) from a collection of monocular 2D images even for topology-varyin…
GRAM-HD: 3D-Consistent Image Generation at High Resolution with Generative Radiance Manifolds
Jianfeng Xiang, Jiaolong Yang, Yu Deng +1
Recent works have shown that 3D-aware GANs trained on unstructured single image collections can generate multiview images of novel instances. The key underpinnings to achieve this…
GRAM: Generative Radiance Manifolds for 3D-Aware Image Generation
Yu Deng, Jiaolong Yang, Jianfeng Xiang +1
3D-aware image generative modeling aims to generate 3D-consistent images with explicitly controllable camera poses. Recent works have shown promising results by training neural rad…
Deformed Implicit Field: Modeling 3D Shapes with Learned Dense Correspondence
Yu Deng, Jiaolong Yang, Xin Tong
We propose a novel Deformed Implicit Field (DIF) representation for modeling 3D shapes of a category and generating dense correspondences among shapes. With DIF, a 3D shape is repr…
Accurate 3D Face Reconstruction with Weakly-Supervised Learning: From Single Image to Image Set
Yu Deng, Jiaolong Yang, Sicheng Xu +3
Recently, deep learning based 3D face reconstruction methods have shown promising results in both quality and efficiency.However, training deep neural networks typically requires a…