Search Results for author:
Found 10 papers, 1 papers with code
PODDP: Partially Observable Differential Dynamic Programming for Latent Belief Space Planning
In this paper, we present an efficient differential dynamic programming (DDP) algorithm for belief space planning in POMDPs with uncertainty over a discrete latent state, and continuous states, actions, observations, and nonlinear dynamics.
Energy-Based Continuous Inverse Optimal Control
The problem of continuous inverse optimal control (over finite time horizon) is to learn the unknown cost function over the sequence of continuous control variables from expert demonstrations.
Multi-Agent Tensor Fusion for Contextual Trajectory Prediction
Specifically, the model encodes multiple agents' past trajectories and the scene context into a Multi-Agent Tensor, then applies convolutional fusion to capture multiagent interactions while retaining the spatial structure of agents and the scene context.
Inferring Forces and Learning Human Utilities From Videos
We propose a notion of affordance that takes into account physical quantities generated when the human body interacts with real-world objects, and introduce a learning framework that incorporates the concept of human utilities, which in our opinion provides a deeper and finer-grained account not only of object affordance but also of people's interaction with objects.
Understanding Tools: Task-Oriented Object Modeling, Learning and Recognition
In this paper, we present a new framework - task-oriented modeling, learning and recognition which aims at understanding the underlying functions, physics and causality in using objects as "tools".
Single-View 3D Scene Parsing by Attributed Grammar
The grammar takes superpixels as its terminal nodes and use five production rules to generate the scene into a hierarchical parse graph.
MILCut: A Sweeping Line Multiple Instance Learning Paradigm for Interactive Image Segmentation
Interactive segmentation, in which a user provides a bounding box to an object of interest for image segmentation, has been applied to a variety of applications in image editing, crowdsourcing, computer vision, and medical imaging.
Beyond Point Clouds: Scene Understanding by Reasoning Geometry and Physics
In this paper, we present an approach for scene understanding by reasoning physical stability of objects from point cloud.
Scene Parsing by Integrating Function, Geometry and Appearance Models
Indoor functional objects exhibit large view and appearance variations, thus are difficult to be recognized by the traditional appearance-based classification paradigm.
Image Parsing with Stochastic Scene Grammar
The algorithm has two stages: (i) Clustering: It forms all possible higher-level structures (clusters) from lower-level entities by production rules and contextual relations.
