activity
20232026
most citedCP-SLAM: Collaborative Neural Point-based SLAM System

3 citations · 3 across the 9 of their papers we have counts for

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13 papers · 1 filter

cs.CV2026

Compact Object-Level Representations with Open-Vocabulary Understanding for Indoor Visual Relocalization

Zhaopeng Cui, Jiarui Hu, Jingbo Liu +7

Indoor visual relocalization plays a critical role in emerging spatial and embodied AI applications. However, prior research was predominantly devoted to low-level vision schemes,…

cs.CV2026

NeuMesh++: Towards Versatile and Efficient Volumetric Editing with Disentangled Neural Mesh-based Implicit Field

Chong Bao, Yuan Li, Bangbang Yang +5

Recently neural implicit rendering techniques have evolved rapidly and demonstrated significant advantages in novel view synthesis and 3D scene reconstruction. However, existing ne…

cs.CV2026

D-Prism: Differentiable Primitives for Structured Dynamic Modeling

Xingyuan Yu, Yijin Li, Chong Zeng +3

Capturing both geometry and rigid motion for structured dynamic objects, like multi-part assemblies or jointed mechanisms, remains a key challenge. Existing dynamic methods, such a…

cs.CV2026

LightCity: An Urban Dataset for Outdoor Inverse Rendering and Reconstruction under Multi-illumination Conditions

Jingjing Wang, Qirui Hu, Chong Bao +4

Inverse rendering in urban scenes is pivotal for applications like autonomous driving and digital twins. Yet, it faces significant challenges due to complex illumination conditions…

cs.CV2025

SGFormer: Satellite-Ground Fusion for 3D Semantic Scene Completion

Xiyue Guo, Jiarui Hu, Junjie Hu +2

Recently, camera-based solutions have been extensively explored for scene semantic completion (SSC). Despite their success in visible areas, existing methods struggle to capture co…

cs.CV2024

A Global Depth-Range-Free Multi-View Stereo Transformer Network with Pose Embedding

Yitong Dong, Yijin Li, Zhaoyang Huang +6

In this paper, we propose a novel multi-view stereo (MVS) framework that gets rid of the depth range prior. Unlike recent prior-free MVS methods that work in a pair-wise manner, ou…