Search Results for author: Justin Kerr

Found 10 papers, 4 papers with code

Splatfacto-W: A Nerfstudio Implementation of Gaussian Splatting for Unconstrained Photo Collections

no code implementations17 Jul 2024 Congrong Xu, Justin Kerr, Angjoo Kanazawa

Novel view synthesis from unconstrained in-the-wild image collections remains a significant yet challenging task due to photometric variations and transient occluders that complicate accurate scene reconstruction.

Novel View Synthesis

GARField: Group Anything with Radiance Fields

1 code implementation CVPR 2024 Chung Min Kim, Mingxuan Wu, Justin Kerr, Ken Goldberg, Matthew Tancik, Angjoo Kanazawa

We optimize this field from a set of 2D masks provided by Segment Anything (SAM) in a way that respects coarse-to-fine hierarchy, using scale to consistently fuse conflicting masks from different viewpoints.

Scene Understanding

Language Embedded Radiance Fields for Zero-Shot Task-Oriented Grasping

no code implementations14 Sep 2023 Adam Rashid, Satvik Sharma, Chung Min Kim, Justin Kerr, Lawrence Chen, Angjoo Kanazawa, Ken Goldberg

Instead, we propose LERF-TOGO, Language Embedded Radiance Fields for Task-Oriented Grasping of Objects, which uses vision-language models zero-shot to output a grasp distribution over an object given a natural language query.

Object

Self-Supervised Learning for Interactive Perception of Surgical Thread for Autonomous Suture Tail-Shortening

no code implementations13 Jul 2023 Vincent Schorp, Will Panitch, Kaushik Shivakumar, Vainavi Viswanath, Justin Kerr, Yahav Avigal, Danyal M Fer, Lionel Ott, Ken Goldberg

Accurate 3D sensing of suturing thread is a challenging problem in automated surgical suturing because of the high state-space complexity, thinness and deformability of the thread, and possibility of occlusion by the grippers and tissue.

Self-Supervised Learning

LERF: Language Embedded Radiance Fields

5 code implementations ICCV 2023 Justin Kerr, Chung Min Kim, Ken Goldberg, Angjoo Kanazawa, Matthew Tancik

Humans describe the physical world using natural language to refer to specific 3D locations based on a vast range of properties: visual appearance, semantics, abstract associations, or actionable affordances.

Nerfstudio: A Modular Framework for Neural Radiance Field Development

2 code implementations8 Feb 2023 Matthew Tancik, Ethan Weber, Evonne Ng, RuiLong Li, Brent Yi, Justin Kerr, Terrance Wang, Alexander Kristoffersen, Jake Austin, Kamyar Salahi, Abhik Ahuja, David McAllister, Angjoo Kanazawa

Neural Radiance Fields (NeRF) are a rapidly growing area of research with wide-ranging applications in computer vision, graphics, robotics, and more.

Dex-NeRF: Using a Neural Radiance Field to Grasp Transparent Objects

1 code implementation27 Oct 2021 Jeffrey Ichnowski, Yahav Avigal, Justin Kerr, Ken Goldberg

The ability to grasp and manipulate transparent objects is a major challenge for robots.

Transparent objects

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