1 citations · 2 across the 10 of their papers we have counts for
12 papers
4LC: 4D Latent Cache for Efficient Conditioning in Dynamic World Modeling
Jianhui Zhang, Zuyao Lin, Pengxin Xu +2
For video generation in dynamic world modeling, observed static and dynamic content should be efficiently reused to provide conditions for repeated generation at different times an…
PINT: A Unified Model with Shared Predictive Intent for Robot Manipulation
Xinyu Guo, Chao Jing, Li Yi +2
Generalist robot manipulation can benefit from pretrained vision-language models (VLMs) for semantic reasoning and video generation models (VGMs) for world modeling. However, exist…
World-Ego Modeling for Embodied Video Generation in Long-Horizon Navigation-Manipulation Tasks
Zuyao Lin, Jianhui Zhang, Peidong Jia +4
Embodied video world models typically capture both scene evolution and the robot's behavior, which we refer to as the \emph{world} and the \emph{ego}, respectively. The world and t…
GeoHand: Unlocking Prior Geometry Knowledge for Monocular 3D Hand Reconstruction
Weiquan Lin, Yaoqing Hu, Liangchen Dai +2
Monocular 3D hand reconstruction is intrinsically a geometric problem, yet RGB appearance features alone often struggle to resolve severe ambiguities caused by self-occlusions and…
SceneParser: Hierarchical Scene Parsing for Visual Semantics Understanding
Pengxin Xu, Xincheng Lin, Luping Xiao +5
General scene perception has progressed from object recognition toward open-vocabulary grounding, part localization, and affordance prediction. Yet these capabilities are often rea…
PriorVLA: Prior-Preserving Adaptation for Vision-Language-Action Models
Xinyu Guo, Bin Xie, Wei Chai +4
Large-scale pretraining has made Vision-Language-Action (VLA) models promising foundations for generalist robot manipulation, yet adapting them to downstream tasks remains necessar…
ECHO: Continuous Hierarchical Memory for Vision-Language-Action Models
Yanbin Hu, Jin Cui, Jiayi Lu +6
Memory capacity is a critical factor determining the performance of Vision-Language-Action (VLA) models in long-horizon manipulation tasks. Existing memory-augmented architectures…
SAM 3D: 3Dfy Anything in Images
SAM 3D Team, Xingyu Chen, Fu-Jen Chu +20
We present SAM 3D, a generative model for visually grounded 3D object reconstruction, predicting geometry, texture, and layout from a single image. SAM 3D excels in natural images,…
Multi-SpatialMLLM: Multi-Frame Spatial Understanding with Multi-Modal Large Language Models
Runsen Xu, Weiyao Wang, Hao Tang +5
Multi-modal large language models (MLLMs) have rapidly advanced in visual tasks, yet their spatial understanding remains limited to single images, leaving them ill-suited for physi…
HOIGPT: Learning Long Sequence Hand-Object Interaction with Language Models
Mingzhen Huang, Fu-Jen Chu, Bugra Tekin +10
We introduce HOIGPT, a token-based generative method that unifies 3D hand-object interactions (HOI) perception and generation, offering the first comprehensive solution for caption…
OmniPose6D: Towards Short-Term Object Pose Tracking in Dynamic Scenes from Monocular RGB
Yunzhi Lin, Yipu Zhao, Fu-Jen Chu +6
To address the challenge of short-term object pose tracking in dynamic environments with monocular RGB input, we introduce a large-scale synthetic dataset OmniPose6D, crafted to mi…
ICON: Incremental CONfidence for Joint Pose and Radiance Field Optimization
Weiyao Wang, Pierre Gleize, Hao Tang +3
Neural Radiance Fields (NeRF) exhibit remarkable performance for Novel View Synthesis (NVS) given a set of 2D images. However, NeRF training requires accurate camera pose for each…