8 papers
MV-SAM: Multi-view Promptable Segmentation using Pointmap Guidance
Yoonwoo Jeong, Cheng Sun, Yu-Chiang Frank Wang +2
Promptable segmentation has emerged as a powerful paradigm in computer vision, enabling users to guide models in parsing complex scenes with prompts such as clicks, boxes, or textu…
Advancing Structured Priors for Sparse-Voxel Surface Reconstruction
Ting-Hsun Chi, Chu-Rong Chen, Chi-Tun Hsu +4
Reconstructing accurate surfaces with radiance fields has progressed rapidly, yet two promising explicit representations, 3D Gaussian Splatting and sparse-voxel rasterization, exhi…
R2SM: Referring and Reasoning for Selective Masks
Yu-Lin Shih, Wei-En Tai, Cheng Sun +2
We introduce a new task, Referring and Reasoning for Selective Masks (R2SM), which extends text-guided segmentation by incorporating mask-type selection driven by user intent. This…
Segment Anything, Even Occluded
Wei-En Tai, Yu-Lin Shih, Cheng Sun +2
Amodal instance segmentation, which aims to detect and segment both visible and invisible parts of objects in images, plays a crucial role in various applications including autonom…
Sparse Voxels Rasterization: Real-time High-fidelity Radiance Field Rendering
Cheng Sun, Jaesung Choe, Charles Loop +2
We propose an efficient radiance field rendering algorithm that incorporates a rasterization process on adaptive sparse voxels without neural networks or 3D Gaussians. There are tw…
SAM4MLLM: Enhance Multi-Modal Large Language Model for Referring Expression Segmentation
Yi-Chia Chen, Wei-Hua Li, Cheng Sun +2
We introduce SAM4MLLM, an innovative approach which integrates the Segment Anything Model (SAM) with Multi-Modal Large Language Models (MLLMs) for pixel-aware tasks. Our method ena…