57 citations · 59 across the 5 of their papers we have counts for
6 papers
Drag4D: Align Your Motion with Text-Driven 3D Scene Generation
Minjun Kang, Inkyu Shin, Taeyeop Lee +2
We introduce Drag4D, an interactive framework that integrates object motion control within text-driven 3D scene generation. This framework enables users to define 3D trajectories f…
BOP Challenge 2024 on Model-Based and Model-Free 6D Object Pose Estimation
Van Nguyen Nguyen, Stephen Tyree, Andrew Guo +16
We present the evaluation methodology, datasets and results of the BOP Challenge 2024, the 6th in a series of public competitions organized to capture the state of the art in 6D ob…
GraspClutter6D: A Large-scale Real-world Dataset for Robust Perception and Grasping in Cluttered Scenes
Seunghyeok Back, Joosoon Lee, Kangmin Kim +8
Robust grasping in cluttered environments remains an open challenge in robotics. While benchmark datasets have significantly advanced deep learning methods, they mainly focus on si…
Any6D: Model-free 6D Pose Estimation of Novel Objects
Taeyeop Lee, Bowen Wen, Minjun Kang +3
We introduce Any6D, a model-free framework for 6D object pose estimation that requires only a single RGB-D anchor image to estimate both the 6D pose and size of unknown objects in…
Category-Level Metric Scale Object Shape and Pose Estimation
Taeyeop Lee, Byeong-Uk Lee, Myungchul Kim +1
Advances in deep learning recognition have led to accurate object detection with 2D images. However, these 2D perception methods are insufficient for complete 3D world information.…
VPGNet: Vanishing Point Guided Network for Lane and Road Marking Detection and Recognition
Seokju Lee, Junsik Kim, Jae Shin Yoon +7
In this paper, we propose a unified end-to-end trainable multi-task network that jointly handles lane and road marking detection and recognition that is guided by a vanishing point…