9 papers · 1 filter
Latent Riemannian Flow Matching for Geometry-Grounded 3D Foundation Models
Lisa Weijler, Irene Ballester, Guofeng Mei +2
Geometric foundation models, such as the Visual Geometry Grounded Transformer (VGGT), provide strong 3D priors from unposed images. However, such models operate purely in a feed-fo…
The Eleventh NTIRE 2026 Efficient Super-Resolution Challenge Report
Bin Ren, Hang Guo, Yan Shu +60
This paper reviews the NTIRE 2026 challenge on efficient single-image super-resolution with a focus on the proposed solutions and results. The aim of this challenge is to devise a…
Efficient Encoder-Free Fourier-based 3D Large Multimodal Model
Guofeng Mei, Wei Lin, Luigi Riz +3
Large Multimodal Models (LMMs) that process 3D data typically rely on heavy, pre-trained visual encoders to extract geometric features. While recent 2D LMMs have begun to eliminate…
GLASS: Graph and Vision-Language Assisted Semantic Shape Correspondence
Qinfeng Xiao, Guofeng Mei, Qilong Liu +5
Establishing dense correspondence across 3D shapes is crucial for fundamental downstream tasks, including texture transfer, shape interpolation, and robotic manipulation. However,…
Action-guided generation of 3D functionality segmentation data
Jaime Corsetti, Francesco Giuliari, Davide Boscaini +6
3D functionality segmentation aims to identify the interactive element in a 3D scene required to perform an action described in free-form language (e.g., the handle to ``Open the s…
Multimodal Fusion SLAM with Fourier Attention
Youjie Zhou, Guofeng Mei, Yiming Wang +2
Visual SLAM is particularly challenging in environments affected by noise, varying lighting conditions, and darkness. Learning-based optical flow algorithms can leverage multiple m…
Parameter-Efficient CLIP Adaptation for 3D Understanding via Unified Tokenization
Guofeng Mei, Qinfeng Xiao, Bin Ren +7
Vision-language models, such as CLIP, encode rich semantic knowledge through large-scale image-text pretraining. Reusing these models for 3D understanding is highly desirable, beca…
PerLA: Perceptive 3D Language Assistant
Guofeng Mei, Wei Lin, Luigi Riz +3
Enabling Large Language Models (LLMs) to understand the 3D physical world is an emerging yet challenging research direction. Current strategies for processing point clouds typicall…
Vocabulary-Free 3D Instance Segmentation with Vision and Language Assistant
Guofeng Mei, Luigi Riz, Yiming Wang +1
Most recent 3D instance segmentation methods are open vocabulary, offering a greater flexibility than closed-vocabulary methods. Yet, they are limited to reasoning within a specifi…