3D Shape Modeling and Analysis

Latest papers

• OptimusMesh: Compact Autoregressive Mesh Generation from Point Clouds via Sparse Latent Pivots

  Mazhar Iqbal, Xuanmeng Sha, Naoya Chiba, Yuki Uranishi, Tomohiro Mashita · 5 October 2026

  Generating compact and geometrically faithful 3D meshes directly from point clouds remains a fundamental challenge. Point clouds are unordered and sparse, whereas meshes exhibit irregular structure and varying topology. As a result, many existing approaches rely on implicit representations followed …

• Transform-Aligned Learned Features for Lossy Point Cloud Attribute Compression

  Yueru Chen, Pengpeng Yu, Dingquan Li, Wei Gao, Wei Zhang, Fei Song · 5 October 2026

  Transform-based methods provide an effective framework for point cloud attribute compression by representing attributes as transform coefficients. Introducing learned spatial context into this framework requires mapping spatial representations to the transform domain, but this known basis change is …

• Unlocking Geodesic Gromov-Wasserstein Distances for 3D Modeling

  Krzysztof Marcin Choromanski, Derek Long, Ananya Parashar, Dwaipayan Saha · 5 October 2026

  \textit{Gromov-Wasserstein Distances} (GWDs) provide quantitative ways of comparing probabilistic distributions defined on different metric spaces by applying techniques from the optimal transport theory. As such, GWD can be potentially useful in a large variety of applications ranging from graph ma…

• I2CD: Direct Image-to-Convex Decomposition for Simulation-Ready Collision Geometry

  Qian Wang, Liam Merz Hoffmeister, Brian Scassellati, Daniel Rakita · 5 October 2026

  Physics simulators and motion planners require convex collision geometry, yet image-to-3D generative models output dense, frequently non-manifold visual meshes. Bridging the two today takes a slow, brittle reconstruct-then-decompose pipeline of repair, decimation, and approximate convex decompositio…

• ManifoldSplat: Language-Guided Semantic Shape Editing of 3D Gaussian Head Avatars

  Antonio Canela, Jordi S\`anchez-Riera · 5 October 2026

  High-fidelity 3D head avatars have reached near-photorealistic quality. While recent methods enable text-driven manipulation, they struggle to provide fine-grained localized control, often entangling features or lacking geometric consistency. Modifying geometry through natural language currently req…

• T3lescope: Arbitrary-Resolution High-Fidelity Generative Surface Reconstruction from Images

  Atsuhiro Noguchi, Tianhan Xu, Yiming Liang, Yuta Kikuchi, Masahiro Ishiyama, Shintaro Takagi, Hitoshi Murai, Eiichi Matsumoto · 5 October 2026

  We reconstruct high-fidelity 3D scene meshes from posed multi-view images without per-scene optimization, across scales ranging from single objects to large outdoor scenes. Per-scene optimization methods lack the learned 3D prior needed when observations are sparse or surfaces are glossy or transpar…

• CrowdOcc: Monocular Semantic Scene Completion for Quadruped Robots in Crowded Indoor Environments

  Feiyang Chen, Jincheng Hu, Yiduo Chen, Jihao Li, Yue Liang, Bingzhao Gao, Yanjun Huang, Yuanjian Zhang · 5 October 2026

  Monocular semantic scene completion (SSC) for quadruped robots remains underexplored in real crowded indoor environments, where human-scene occlusion disrupts static geometry and human occupancy predictions are often incomplete or spatially misplaced. We present CrowdOcc, an RGB-D dataset and monocu…

• Octrees as an Explicit 3D Language

  Ran Dan, Si-Tong Wei, Pengfei Xiong, Wei Zhang, Yadong Mu, Peng-Shuai Wang · 5 October 2026

  Existing 3D large language models (LLMs) compromise on two fronts: they compress shapes into latent codebook indices or coordinate text, which removes spatial structure from what the model observes, and they acquire the 3D modality by fine-tuning the backbone, which overwrites its general language a…

• SCION: Scene Composition with Instanced Neural Primitives

  William Koch, Amogh Joshi, Cyrus Vachha, Cheng Zheng, Felix Heide · 5 October 2026

  Real-world scenes are compositional: bricks, blades of grass, pebbles, and tree leaves recur across human-built and natural environments. Existing neural scene representations model these elements independently. Most 3D Gaussian Splatting and follow-up abstraction and compression methods treat each …

• Less Decoder is More Encoder: Geometric Representation Learning from Novel View Synthesis

  Keerthi Kaashyap, Dennis Anthony, Akshay Krishnan, Nhi Ngoc Nguyen, Jeremy Collins, James Hays, Shreyas Kousik, Animesh Garg · 5 October 2026

  This paper examines the role of Novel View Synthesis (NVS) in geometric representation learning. In principle, NVS should reason about 3D scene structure, thereby enabling transferable multi-view geometric representations. Yet, existing encoder-based NVS methods yield poor representations. This is n…

• SILSA: Sliding-Window Slice Latents for Topology-Preserving High-Resolution 3D Generation

  Tianjiao Yu, Xinzhuo Li, Yifan Shen, Ying Shen, Kiet A. Nguyen, Adheesh Sunil Juvekar, Ismini Lourentzou · 2 October 2026

  High-resolution 3D generation increasingly relies on voxel latents and multi-stage pipelines that first predict active structure and then synthesize local geometry. While effective, this design fragments continuous surfaces into many local tokens, inflates generation cost, and often weakens topologi…

• SPHERE: Adaptive VR Indoor Scene Generation via LLM-Enhanced Spatial Preference Learning and Human-in-the-Loop RL

  Hyeonmin Lee, Zheng Wei, Kyungmin Kwon, Jumin Seo, Jiwon Park, Hayoung Oh · 2 October 2026

  While Large Language Models (LLMs) advance 3D indoor scene synthesis, current pipelines fail to retain user-specific preferences across sessions, making immersive authoring a repetitive and physically fatiguing process. We present SPHERE, an adaptive VR generation framework that transforms isolated …

• SPOON: Towards Coherent Compositional 3D Scene Generation from Uncalibrated Multi-view Images

  Guibiao Liao, Mochu Xiang, Heng Li, Ken Deng, Zijie Wang, Guanbin Li, Ping Tan, Shenghua Gao, Yizhou Yu · 1 October 2026

  Compositional 3D scene generation aims to recover complete 3D object shapes and their spatial arrangement from visual observations. Recent image-conditioned 3D generators provide strong priors for producing high-quality object geometry, making the generation of complex scenes increasingly practical.…

• MeshOctave generates meshes via cascading resolution transitions

  Junkai Lin, Tianhao Zhao, Hang Long, Huipeng Guo, Jielei Zhang, Youjia Zhang, Jiale Xu, Wenbing Li, Rendong Liang, Jozef Hladk\'y, Matthias Nie{\ss}ner, Yuanming Hu, Wei Yang · 1 October 2026

  Generating compact, artist-style meshes with explicit topology typically relies on autoregressive models which incur prohibitive sequential per-token costs, or continuous flow models that depend on heuristic connectivity decoders. Next-scale generation paradigms offer a compelling alternative by ena…

• AdaOcc: Adaptive 3D Occupancy Prediction for Embodied Tasks

  Jinglong Wang, Yunjie Wang, Zhiyang Zhang, Jiawei He, Ye Yuan, Bo Qiu, Jing Zhang · 1 October 2026

  Embodied tasks demand accurate, flexible, and semantically rich 3D scene representations. 3D semantic occupancy is well suited to this requirement, as it can model holistic 3D spaces by encoding geometric occupancy along with semantic categories. However, existing occupancy prediction methods strugg…

• HIGS: Hierarchical Implicit Grids for Joint Geometric and Semantic Scene Understanding

  Hanwen Cao, Wenqiang Wu, Kuang-Ting Tu, Mathias Otnes, Jeffrey Delmerico, Rui Wang, Yulun Tian, Nikolay Atanasov · 1 October 2026

  Neural implicit representations have had a significant impact on scene reconstruction by enabling robots to build continuous, differentiable, and high-fidelity 3D maps. Most existing works focus on geometric reconstruction and lack semantic information for high-level spatial understanding and task p…

• CoDimRecon: Agentic Reconstruction of Sim-Ready 3D Scenes with Deformable Curves, Surfaces, and Volumes

  Shuzhao Xie, Lelin Wang, Guying Lin, Zhi Wang, Minchen Li · 30 September 2026

  Reconstructing simulation-ready 3D scenes from real-world observations enables robotics, gaming, and immersive applications, yet existing methods largely assume rigid objects. This leaves an important gap for deformables, whose simulation-ready geometry depends on dimensionality (curves, surfaces, o…

• VGGT-Diff: Visual Geometry Meets Diffusion for Sparse-View Novel View Synthesis

  Kangjie Chen, Xiangyu Li, Dongbin Zhang, Chaoda Zheng, Shijia Chen, Jinhao Deng, Hongbin Lin, Choo Sin Wai, Minqi Wang, Minghao Yang, Dake Zhong, Guorui Song, Yu Zhang, Xianming Liu, Boyang Wang · 29 September 2026

  We present VGGT-Diff, a geometry-routed multi-view diffusion model for sparse-view novel view synthesis. Existing novel view synthesis (NVS) methods face a fundamental trade-off: reconstruction-based approaches preserve observed geometry but struggle to synthesize unseen regions, while diffusion-bas…

• GraphWrit3R: End-to-End 3D Scene Graph Writing

  Luka Milivojevic, Nikola Popovic, Sayan Deb Sarkar, Sebastian Koch, Iro Armeni, Luc Van Gool, Danda Pani Paudel · 28 September 2026

  3D scene graphs provide a structured representation of complex environments by encoding objects, their semantic attributes, and the spatial and functional relationships between them. Current approaches for 3D scene graph generation suffer from several fundamental limitations. They rely on complex mu…

• M3GD: Multi-Modal Multi-View Geometric Diffusion for Camera--LiDAR Novel View Synthesis

  Yang Zhou, Jiuhong Xiao, Shizhao Ye, Long Quang, Carlos Nieto-Granda, Giuseppe Loianno · 25 September 2026

  Robotic novel view synthesis (NVS) must recover both visual appearance and metric 3D structure, yet most generative NVS methods rely only on images, overlooking LiDAR, a complementary sensor common on robotic platforms. We present M3GD, a Camera--LiDAR multimodal representation for generative NVS th…

• ToCo-Mesh: Topology-Consistent Dynamic Mesh Reconstruction via Adaptive Tessellation and Surface-Aligned 2DGS

  Chuanjin Fan, Wenjie Chang, Aibing Li, Bingzhou Wang, Wenfei Yang, Tianzhu Zhang · 25 September 2026

  Reconstructing dynamic meshes with consistent topology from multi-view temporal images remains a challenge. Existing approaches typically face a dilemma between fine-scale shape recovery and topological stability. Frame-by-frame extraction methods capture fine details but break vertex correspondence…

• SplatLabel: Pseudo-Labelling through 4D Gaussian Splatting

  Nitya Nanvani, Andras Palffy, Holger Caesar · 25 September 2026

  While 2D Vision Foundation Models offer a pathway to automate 3D semantic pseudo-labelling, translating these priors into robust 3D representations typically requires complex heuristics or multi-model ensembles. We introduce SplatLabel, an automated pipeline that leverages a 4D Gaussian representati…

• OREO: Fidelity Alignment in 3D Generation via On-the-fly Rendering-Editing Optimization

  Zhiyuan Ma, Wenbo Hu, Wang Zhao, Pengfei Wang, Ying Shan, Lei Zhang · 25 September 2026

  Despite recent advancements in 3D generation, models often struggle to produce assets with high visual fidelity. To bridge this gap, we propose OREO, an alignment framework that enhances the realism of 3D generators by leveraging rich 2D diffusion priors. Instead of relying on static datasets, OREO …

• M-plicits: Neural Implicit Surfaces via Nested Multiscale Residuals

  Vin\'icius da Silva, Isabelle Melo, Matheus Bessa, Guilherme Schardong, Luiz Schirmer, Andr\'e Ara\'ujo, Nuno Gon\c{c}alves, H\'elio Lopes, Alberto Raposo, Luiz Velho, Tiago Novello · 25 September 2026

  Encoding input coordinates with sinusoidal functions into multi-layer perceptrons (MLPs) has proven effective for implicit neural representations (INRs) of surfaces defined as zero-level sets. However, existing methods often struggle to balance training efficiency, rendering speed, and noise robustn…

• PePESeg3D: Perception Prior Enhances Multi-Scale Segmentation for 3D Gaussian Splatting

  Sungjae Choi, Seunghee Koh, Junmo Kim · 25 September 2026

  Recent advancements in 3D Gaussian Splatting (3DGS) have extended its capabilities to multi-scale segmentation. Existing methods reconstruct a scene with Gaussian primitives and learn multi-scale segmentation features separately, which leaves the geometry unaware of semantic structure and the featur…