1 citations · 2 across the 16 of their papers we have counts for
7 papers · 1 filter
Enhancing Part-Level Point Grounding for Any Open-Source MLLMs
Jin-Cheng Jhang, Fu-En Wang, Xin Yang +4
Visual grounding aims to associate free-form textual queries with specific regions in an image. While recent Multimodal Large Language Models (MLLMs) have demonstrated promising ca…
OpenM3D: Open Vocabulary Multi-view Indoor 3D Object Detection without Human Annotations
Peng-Hao Hsu, Ke Zhang, Fu-En Wang +6
Open-vocabulary (OV) 3D object detection is an emerging field, yet its exploration through image-based methods remains limited compared to 3D point cloud-based methods. We introduc…
Details Matter for Indoor Open-vocabulary 3D Instance Segmentation
Sanghun Jung, Jingjing Zheng, Ke Zhang +10
Unlike closed-vocabulary 3D instance segmentation that is often trained end-to-end, open-vocabulary 3D instance segmentation (OV-3DIS) often leverages vision-language models (VLMs)…
UA-Pose: Uncertainty-Aware 6D Object Pose Estimation and Online Object Completion with Partial References
Ming-Feng Li, Xin Yang, Fu-En Wang +5
6D object pose estimation has shown strong generalizability to novel objects. However, existing methods often require either a complete, well-reconstructed 3D model or numerous ref…
POp-GS: Next Best View in 3D-Gaussian Splatting with P-Optimality
Joey Wilson, Marcelino Almeida, Sachit Mahajan +6
In this paper, we present a novel algorithm for quantifying uncertainty and information gained within 3D Gaussian Splatting (3D-GS) through P-Optimality. While 3D-GS has proven to…
V-MIND: Building Versatile Monocular Indoor 3D Detector with Diverse 2D Annotations
Jin-Cheng Jhang, Tao Tu, Fu-En Wang +3
The field of indoor monocular 3D object detection is gaining significant attention, fueled by the increasing demand in VR/AR and robotic applications. However, its advancement is i…