collaborators
Showing cs.CVShow all

6 papers · 1 filter

cs.CV2026

Faster-WAM: Efficient Inference-Time Future Conditioning for Robust World Action Models

Weiheng Zhao, Haoyi Jiang, Xin Shi +5

World Action Models (WAMs) improve robot manipulation by learning how the environment evolves beyond the current observation. However, existing approaches face a fundamental dilemm…

cs.CV2026

3D-Fixer: Coarse-to-Fine In-place Completion for 3D Scenes from a Single Image

Ze-Xin Yin, Liu Liu, Xinjie Wang +4

Compositional 3D scene generation from a single view requires the simultaneous recovery of scene layout and 3D assets. Existing approaches mainly fall into two categories: feed-for…

cs.CV2026

DreamLifting: A Plug-in Module Lifting MV Diffusion Models for 3D Asset Generation

Ze-Xin Yin, Jiaxiong Qiu, Liu Liu +5

The labor- and experience-intensive creation of 3D assets with physically based rendering (PBR) materials demands an autonomous 3D asset creation pipeline. However, most existing 3…

cs.CV2026

IRIS-SLAM: Unified Geo-Instance Representations for Robust Semantic Localization and Mapping

Tingyang Xiao, Liu Liu, Wei Feng +6

Geometry foundation models have significantly advanced dense geometric SLAM, yet existing systems often lack deep semantic understanding and robust loop closure capabilities. Meanw…

cs.CV2026

Uni3R: Unified 3D Reconstruction and Semantic Understanding via Generalizable Gaussian Splatting from Unposed Multi-View Images

Xiangyu Sun, Haoyi Jiang, Liu Liu +8

Reconstructing and semantically interpreting 3D scenes from sparse 2D views remains a fundamental challenge in computer vision. Conventional methods often decouple semantic underst…

cs.CV2026

Spa3R: Predictive Spatial Field Modeling for 3D Visual Reasoning

Haoyi Jiang, Liu Liu, Xinjie Wang +5

Vision-language models excel at 2D visual understanding but remain limited in 3D spatial reasoning. Existing approaches either depend on explicit 3D modalities, which limits scalab…