7 citations · 20 across the 10 of their papers we have counts for
10 papers
Streaming Flow Policy: Simplifying diffusion/flow-matching policies by treating action trajectories as flow trajectories
Sunshine Jiang, Xiaolin Fang, Nicholas Roy +3
Recent advances in diffusionflow-matching policies have enabled imitation learning of complex, multi-modal action trajectories. However, they are computationally expensive becau…
Keypoint Abstraction using Large Models for Object-Relative Imitation Learning
Xiaolin Fang, Bo-Ruei Huang, Jiayuan Mao +4
Generalization to novel object configurations and instances across diverse tasks and environments is a critical challenge in robotics. Keypoint-based representations have been prov…
Embodied Uncertainty-Aware Object Segmentation
Xiaolin Fang, Leslie Pack Kaelbling, Tomás Lozano-Pérez
We introduce uncertainty-aware object instance segmentation (UncOS) and demonstrate its usefulness for embodied interactive segmentation. To deal with uncertainty in robot percepti…
DiMSam: Diffusion Models as Samplers for Task and Motion Planning under Partial Observability
Xiaolin Fang, Caelan Reed Garrett, Clemens Eppner +3
Generative models such as diffusion models, excel at capturing high-dimensional distributions with diverse input modalities, e.g. robot trajectories, but are less effective at mult…
Long-Horizon Manipulation of Unknown Objects via Task and Motion Planning with Estimated Affordances
Aidan Curtis, Xiaolin Fang, Leslie Pack Kaelbling +2
We present a strategy for designing and building very general robot manipulation systems involving the integration of a general-purpose task-and-motion planner with engineered and…
Learning Cycle-Consistent Cooperative Networks via Alternating MCMC Teaching for Unsupervised Cross-Domain Translation
Jianwen Xie, Zilong Zheng, Xiaolin Fang +2
This paper studies the unsupervised cross-domain translation problem by proposing a generative framework, in which the probability distribution of each domain is represented by a g…
Cooperative Training of Fast Thinking Initializer and Slow Thinking Solver for Conditional Learning
Jianwen Xie, Zilong Zheng, Xiaolin Fang +2
This paper studies the problem of learning the conditional distribution of a high-dimensional output given an input, where the output and input may belong to two different domains,…
Divergence Triangle for Joint Training of Generator Model, Energy-based Model, and Inference Model
Tian Han, Erik Nijkamp, Xiaolin Fang +3
This paper proposes the divergence triangle as a framework for joint training of generator model, energy-based model and inference model. The divergence triangle is a compact and s…
Weakly and Semi Supervised Human Body Part Parsing via Pose-Guided Knowledge Transfer
Hao-Shu Fang, Guansong Lu, Xiaolin Fang +3
Human body part parsing, or human semantic part segmentation, is fundamental to many computer vision tasks. In conventional semantic segmentation methods, the ground truth segmenta…
Recurrent Residual Module for Fast Inference in Videos
Bowen Pan, Wuwei Lin, Xiaolin Fang +3
Deep convolutional neural networks (CNNs) have made impressive progress in many video recognition tasks such as video pose estimation and video object detection. However, CNN infer…