2 citations · 4 across the 14 of their papers we have counts for
15 papers
STEREOFLOW: Progressive Stereo Matching with StereoDiT and Transition Flow Matching
Hao Wang, Haoran Geng, Xiaotong Yang +7
Stereo matching is a fundamental task in 3D reconstruction. Despite remarkable advances, the prevailing paradigms formulate stereo matching as a deterministic regression problem, c…
SIMPLE: Simulation-Based Policy Learning and Evaluation for Humanoid Loco-manipulation
Songlin Wei, Zhenhao Ni, Jie Liu +9
Humanoid foundation models are advancing faster than we can evaluate them. While real-world testing is expensive and difficult to reproduce, existing simulation benchmarks focus pr…
: An Open Foundation Model Towards Universal Humanoid Loco-Manipulation
Songlin Wei, Hongyi Jing, Boqian Li +12
We introduce (Psi-Zero), an open foundation model to address challenging humanoid loco-manipulation tasks. While existing approaches often attempt to address this fundamental…
ICLR: In-Context Imitation Learning with Visual Reasoning
Toan Nguyen, Weiduo Yuan, Songlin Wei +3
In-context imitation learning enables robots to adapt to new tasks from a small number of demonstrations without additional training. However, existing approaches typically conditi…
Diffusion Knows Transparency: Repurposing Video Diffusion for Transparent Object Depth and Normal Estimation
Shaocong Xu, Songlin Wei, Qizhe Wei +12
Transparent objects remain notoriously hard for perception systems: refraction, reflection and transmission break the assumptions behind stereo, ToF and purely discriminative monoc…
Unrolling Nonconvex Graph Total Variation for Image Denoising
Songlin Wei, Gene Cheung, Fei Chen +1
Conventional model-based image denoising optimizations employ convex regularization terms, such as total variation (TV) that convexifies the -norm to promote sparse signal…
GraspVLA: a Grasping Foundation Model Pre-trained on Billion-scale Synthetic Action Data
Shengliang Deng, Mi Yan, Songlin Wei +10
Embodied foundation models are gaining increasing attention for their zero-shot generalization, scalability, and adaptability to new tasks through few-shot post-training. However,…
RoboVerse: Towards a Unified Platform, Dataset and Benchmark for Scalable and Generalizable Robot Learning
Haoran Geng, Feishi Wang, Songlin Wei +34
Data scaling and standardized evaluation benchmarks have driven significant advances in natural language processing and computer vision. However, robotics faces unique challenges i…
Uni-NaVid: A Video-based Vision-Language-Action Model for Unifying Embodied Navigation Tasks
Jiazhao Zhang, Kunyu Wang, Shaoan Wang +6
A practical navigation agent must be capable of handling a wide range of interaction demands, such as following instructions, searching objects, answering questions, tracking peopl…
RoboHanger: Learning Generalizable Robotic Hanger Insertion for Diverse Garments
Yuxing Chen, Songlin Wei, Bowen Xiao +4
For the task of hanging clothes, learning how to insert a hanger into a garment is a crucial step, but has rarely been explored in robotics. In this work, we address the problem of…
GAPartManip: A Large-scale Part-centric Dataset for Material-Agnostic Articulated Object Manipulation
Wenbo Cui, Chengyang Zhao, Songlin Wei +5
Effectively manipulating articulated objects in household scenarios is a crucial step toward achieving general embodied artificial intelligence. Mainstream research in 3D vision ha…
D3RoMa: Disparity Diffusion-based Depth Sensing for Material-Agnostic Robotic Manipulation
Songlin Wei, Haoran Geng, Jiayi Chen +6
Depth sensing is an important problem for 3D vision-based robotics. Yet, a real-world active stereo or ToF depth camera often produces noisy and incomplete depth which bottlenecks…
SAGE: Bridging Semantic and Actionable Parts for GEneralizable Manipulation of Articulated Objects
Haoran Geng, Songlin Wei, Congyue Deng +3
To interact with daily-life articulated objects of diverse structures and functionalities, understanding the object parts plays a central role in both user instruction comprehensio…
Make a Donut: Hierarchical EMD-Space Planning for Zero-Shot Deformable Manipulation with Tools
Yang You, Bokui Shen, Congyue Deng +4
Deformable object manipulation stands as one of the most captivating yet formidable challenges in robotics. While previous techniques have predominantly relied on learning latent d…
FG-NeRF: Flow-GAN based Probabilistic Neural Radiance Field for Independence-Assumption-Free Uncertainty Estimation
Songlin Wei, Jiazhao Zhang, Yang Wang +3
Neural radiance fields with stochasticity have garnered significant interest by enabling the sampling of plausible radiance fields and quantifying uncertainty for downstream tasks.…