4 citations · 8 across the 12 of their papers we have counts for
14 papers · 1 filter
ConceptPose: Training-Free Zero-Shot Object Pose Estimation using Concept Vectors
Liming Kuang, Yordanka Velikova, Mahdi Saleh +3
Object pose estimation is a fundamental task in computer vision and robotics, yet most methods require extensive, dataset-specific training. Concurrently, large-scale vision langua…
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…
From Scan to Action: Leveraging Realistic Scans for Embodied Scene Understanding
Anna-Maria Halacheva, Jan-Nico Zaech, Sombit Dey +2
Real-world 3D scene-level scans offer realism and can enable better real-world generalizability for downstream applications. However, challenges such as data volume, diverse annota…
GaussianVLM: Scene-centric 3D Vision-Language Models using Language-aligned Gaussian Splats for Embodied Reasoning and Beyond
Anna-Maria Halacheva, Jan-Nico Zaech, Xi Wang +2
As multimodal language models advance, their application to 3D scene understanding is a fast-growing frontier, driving the development of 3D Vision-Language Models (VLMs). Current…
Occam's LGS: An Efficient Approach for Language Gaussian Splatting
Jiahuan Cheng, Jan-Nico Zaech, Luc Van Gool +1
TL;DR: Gaussian Splatting is a widely adopted approach for 3D scene representation, offering efficient, high-quality reconstruction and rendering. A key reason for its success is t…
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…