no code implementations • 14 Dec 2023 • Hongsuk Choi, Isaac Kasahara, Selim Engin, Moritz Graule, Nikhil Chavan-Dafle, Volkan Isler
While ControlNet provides control over the geometric form of the instances in the generated image, it lacks the capability to dictate the visual appearance of each instance.
no code implementations • 8 Nov 2023 • Jun-Jee Chao, Selim Engin, Nikhil Chavan-Dafle, Bhoram Lee, Volkan Isler
We study the problem of aligning a video that captures a local portion of an environment to the 2D LiDAR scan of the entire environment.
no code implementations • 14 Sep 2023 • Hongsuk Choi, Nikhil Chavan-Dafle, Jiacheng Yuan, Volkan Isler, Hyunsoo Park
The inference as well as training-data generation for 3D hand-object scene reconstruction is challenging due to the depth ambiguity of a single image and occlusions by the hand and object.
no code implementations • 24 Jul 2023 • Maria Bauza, Antonia Bronars, Yifan Hou, Ian Taylor, Nikhil Chavan-Dafle, Alberto Rodriguez
We propose simPLE (simulation to Pick Localize and PLacE) as a solution to precise pick-and-place.
no code implementations • 21 Jul 2023 • Isaac Kasahara, Shubham Agrawal, Selim Engin, Nikhil Chavan-Dafle, Shuran Song, Volkan Isler
General scene reconstruction refers to the task of estimating the full 3D geometry and texture of a scene containing previously unseen objects.
1 code implementation • 16 May 2023 • Shubham Agrawal, Nikhil Chavan-Dafle, Isaac Kasahara, Selim Engin, Jinwook Huh, Volkan Isler
In this paper, we present a novel method to provide this geometric and semantic information of all objects in the scene as well as feasible grasps on those objects simultaneously.