1 citations · 1 across the 4 of their papers we have counts for
5 papers
PAWS: Perception of Articulation in the Wild at Scale from Egocentric Videos
Yihao Wang, Yang Miao, Wenshuai Zhao +8
Articulation perception aims to recover the motion and structure of articulated objects (e.g., drawers and cupboards), and is fundamental to 3D scene understanding in robotics, sim…
LangHOPS: Language Grounded Hierarchical Open-Vocabulary Part Segmentation
Yang Miao, Jan-Nico Zaech, Xi Wang +3
We propose LangHOPS, the first Multimodal Large Language Model (MLLM) based framework for open-vocabulary object-part instance segmentation. Given an image, LangHOPS can jointly de…
EgoNight: Towards Egocentric Vision Understanding at Night with a Challenging Benchmark
Deheng Zhang, Yuqian Fu, Runyi Yang +9
Most existing benchmarks for understanding egocentric vision focus primarily on daytime scenarios, overlooking the low-light conditions that are inevitable in real-world applicatio…
Articulate3D: Holistic Understanding of 3D Scenes as Universal Scene Description
Anna-Maria Halacheva, Yang Miao, Jan-Nico Zaech +3
3D scene understanding is a long-standing challenge in computer vision and a key component in enabling mixed reality, wearable computing, and embodied AI. Providing a solution to t…
SceneGraphLoc: Cross-Modal Coarse Visual Localization on 3D Scene Graphs
Yang Miao, Francis Engelmann, Olga Vysotska +3
We introduce a novel problem, i.e., the localization of an input image within a multi-modal reference map represented by a database of 3D scene graphs. These graphs comprise multip…