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Found 10 papers, 0 papers with code
GenCHiP: Generating Robot Policy Code for High-Precision and Contact-Rich Manipulation Tasks
Large Language Models (LLMs) have been successful at generating robot policy code, but so far these results have been limited to high-level tasks that do not require precise movement.
Teaching Compositionality to CNNs
Convolutional neural networks (CNNs) have shown great success in computer vision, approaching human-level performance when trained for specific tasks via application-specific loss functions.
Image Retrieval Using Scene Graphs
We introduce a novel dataset of 5, 000 human-generated scene graphs grounded to images and use this dataset to evaluate our method for image retrieval.
Enriching Object Detection With 2D-3D Registration and Continuous Viewpoint Estimation
We propose an efficient method for synthesizing templates from 3D models that runs on the fly -- that is, it quickly produces detectors for an arbitrary viewpoint of a 3D model without expensive dataset-dependent training or template storage.
3D Object Class Detection in the Wild
Object class detection has been a synonym for 2D bounding box localization for the longest time, fueled by the success of powerful statistical learning techniques, combined with robust image representations.
Towards Scene Understanding with Detailed 3D Object Representations
An object class - in our case cars - is modeled as a deformable 3D wireframe, which enables fine-grained modeling at the level of individual vertices and faces.
Are Cars Just 3D Boxes? - Jointly Estimating the 3D Shape of Multiple Objects
Current systems for scene understanding typically represent objects as 2D or 3D bounding boxes.
Multi-View Priors for Learning Detectors from Sparse Viewpoint Data
While the majority of today's object class models provide only 2D bounding boxes, far richer output hypotheses are desirable including viewpoint, fine-grained category, and 3D geometry estimate.
Explicit Occlusion Modeling for 3D Object Class Representations
In this paper, we tackle the challenge of modeling occlusion in the context of a 3D geometric object class model that is capable of fine-grained, part-level 3D object reconstruction.
Occlusion Patterns for Object Class Detection
Despite the success of recent object class recognition systems, the long-standing problem of partial occlusion remains a major challenge, and a principled solution is yet to be found.
