4 papers · 1 filter
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)…
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…
BaFTA: Backprop-Free Test-Time Adaptation For Zero-Shot Vision-Language Models
Xuefeng Hu, Ke Zhang, Min Sun +3
Large-scale pretrained vision-language models like CLIP have demonstrated remarkable zero-shot image classification capabilities across diverse domains. To enhance CLIP's performan…