3D Reconstruction

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3D reconstruction studies how to infer the shape and appearance of objects or scenes, along with camera positions and motion, from partial observations. Methods range from structure-from-motion and multi-view stereo to neural radiance fields, Gaussian splatting, signed distance fields, meshes, and feed-forward models that predict geometry directly; some also use diffusion priors, active view selection, or physical sensor models. Applications include mapping and robotics, digital twins, medical imaging, and human or object modeling, with evaluations often comparing both rendered views and geometric accuracy on indoor, outdoor, and specialized datasets. A central challenge is that realistic novel-view images do not always imply accurate, metrically consistent geometry, especially with sparse or unposed views, changing scenes, difficult materials, or limited computation.

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971 papers93 papers in the last four weeks, down 17% on the four weeks before. 0.6% of all new papers.

MetricHMSR:Metric Human Mesh and Scene Recovery from Monocular Images
Jun 11, 2025Chentao Song, He Zhang, Haolei Yuan +4Metric Depth Estimation 3D Reconstruction
Tsinghua University · Beihang University · Beijing Normal University
Synthetic Enclosed Echoes: A New Dataset to Mitigate the Gap Between Simulated and Real-World Sonar Data
May 21, 2025Guilherme de Oliveira, Matheus M. dos Santos, Paulo L. J. Drews-JrSynthetic-to-Real Domain Adaptation Underwater Imaging
NAUTEC - Intelligent robotics and automation group, FURG - Federal University of Rio Grande, Rio Grande, RS, Brazil · ICMC - Institute of Mathematics and Computer Sciences, USP - University of S˜ao Paulo, S˜ao Carlos, SP, Brazil
TUGS: Physics-based Compact Representation of Underwater Scenes by Tensorized Gaussian
May 12, 2025Shijie Lian, Ziyi Zhang, Hua Li +43D Gaussian Splatting Underwater Imaging
1Huazhong University of Science and Technology · 2Zhongguancun Academy · 3The Chinese University of Hong Kong, Shenzhen +3
CATSplat: Context-Aware Transformer with Spatial Guidance for Generalizable 3D Gaussian Splatting from A Single-View Image
Dec 17, 2024Wonseok Roh, Hwanhee Jung, Jong Wook Kim +63D Gaussian Splatting 3D ViTs
Korea University · Google · Purdue University
Sonicmesh: Enhancing 3D Human Mesh Reconstruction in Vision-Impaired Environments With Acoustic Signals
Dec 15, 2024Xiaoxuan Liang, Hong Zhou, Zhaolong Wei +33D Reconstruction Human Mesh Recovery
University of Massachusetts at Amherst, Location, Country · Trine University · University of Illinois at Chicago +1
SparseLGS: Sparse View Language Embedded Gaussian Splatting
Dec 3, 2024Jun Hu, Zhang Chen, Zhong Li +23D Gaussian Splatting Language-Embedded 3DGS
School of Mathematical Science, University of Science and Technology of China · Meta · Apple Inc. +1
NumGrad-Pull: Numerical Gradient Guided Tri-plane Representation for Surface Reconstruction from Point Clouds
Nov 26, 2024Ruikai Cui, Binzhu Xie, Shi Qiu +3Implicit Neural Representations 3D Reconstruction
School of Computing, The Australian National University, Australia · Department of Computer Science and Engineering, The Chinese University of Hong Kong, Hong Kong SAR, China · Department of Computer Science & Software Engineering, the University of Western Australia, Australia
GSurf: Learning Signed Distance Fields from Splatting Opaque Gaussians for High-quality 3D Reconstruction
Nov 24, 2024Baixin Xu, Jiangbei Hu, Jiaze Li +13D Gaussian Splatting Signed Distance Functions
College of Computing and Data Science, Nanyang Technological University · School of Software, Dalian University of Technology
PSHuman: Photorealistic Single-image 3D Human Reconstruction using Cross-Scale Multiview Diffusion and Explicit Remeshing
Sep 16, 2024Peng Li, Wangguandong Zheng, Yuan Liu +9Multi-View Diffusion Models 3D Reconstruction
HKUST · Southeast University · Tsinghua University +1
2DGH: 2D Gaussian-Hermite Splatting for High-quality Rendering and Better Geometry Features
Aug 30, 2024Ruihan Yu, Tianyu Huang, Jingwang Ling +13D Gaussian Splatting 3D Reconstruction
Department of Physics, Tsinghua University · School of software and BNRist, Tsinghua University
Multi-view Hand Reconstruction with a Point-Embedded Transformer
Aug 20, 2024Lixin Yang, Licheng Zhong, Pengxiang Zhu +43D ViTs Markerless Motion Capture
School of Artificial Intelligence (SAI), Shanghai Jiao Tong University, Shanghai 200230, China · School of Mechanical Engineering, Shanghai Jiao Tong University, Shanghai 200240, China · School of Electronic Information and Electrical Engineering, Shanghai Jiao Tong University, Shanghai 200240, China +1

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MetricHMSR:Metric Human Mesh and Scene Recovery from Monocular Images

Chentao Song, He Zhang, Haolei Yuan, Haozhe Lin+3

Tsinghua University · Beihang University · Beijing Normal University

Metric Depth Estimation 3D Reconstruction Depth Estimation Human Mesh Recovery Monocular 3D Reconstruction 3D Mesh Reconstruction+1

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We introduce MetricHMSR, a novel framework for recovering metric human meshes and 3D scenes from a single monocular image. Existing methods struggle to recover metric scale due to monocular scale ambiguity and weak-perspective camera assumptions. Moreover, their fully coupled feature representations make it difficult to disentangle local pose from global translation, often requiring multi-stage pipelines that introduce accumulated errors. To address these challenges, we propose MetricHMR (Metric Human Mesh Recovery), which incorporates a bounding camera ray map representation to provide explicit metric cues for human reconstruction,together with a Human Mixture-of-Experts (HumanMoE) that dynamically routes image features to specialized experts, enabling the disentangled perception of local human pose and global metric position. Leveraging the recovered metric human as a geometric anchor, we further refine monocular metric depth estimation to achieve more accurate 3D alignment between humans and scenes.Comprehensive experiments demonstrate that our method achieves state-of-the-art performance on both human mesh recovery and metric human-scene reconstruction. Project Page: https://Metaverse-AI-Lab-THU.github.io/MetricHMSR.