3D Diffusion Models

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14 papers in the last four weeks, up 250% on the four weeks before. 0.1% of all new papers.

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TCAM-Diff: Triplane-Aware Cross-Attention Medical Diffusion Model
Jul 15, 2026Zhenkai Zhang, Krista A. Ehinger, Tom Drummond3D Medical Imaging Medical Image Synthesis
School of Computing and Information Systems, The University of Melbourne · The University of Melbourne
Nexus: Native Mesh Generation with Diffusion
Jul 15, 2026Hanxiao Wang, Ying-Tian Liu, Yuan-Chen Guo +53D Mesh Generation 3D Shape Generation
MAIS, Institute of Automation, Chinese Academy of Sciences; School of Artificial Intelligence, University of Chinese Academy of Sciences, China · VAST, China · Tsinghua University, China +1
DiffGI: Differentiable Geometry Images for High-Fidelity Thin-Shell 3D Generation
Jul 15, 2026Eungjune Shim, Hansol Lee, Eunjung Ju3D Mesh Generation 3D Shape Generation
CLO Virtual Fashion Inc., South Korea
EquiFusion: Kinematics-Agnostic Human Motion Prediction via Equivariant Latent Diffusion
Jul 13, 2026Cecilia Curreli, Florian Hofherr, Dominik Muhle +3Equivariant Neural Networks Human Motion Prediction
Technical University of Munich, Munich, Germany · Munich Center for Machine Learning, Munich, Germany
3D Scene Graph Prediction: Generating Hierarchical Models from Partially Observed Environments
Jul 12, 2026Siyi H, Jared Strade, Hyungtae Lim +13D SGG 3D Scene Layout Generation
Laboratory for Information & Decision Systems (LIDS), Massachusetts Institute of Technology, Cambridge, MA 02139, USA. · Department of Electrical and Computer Engineering, Oakland University, Rochester, MI 48309, USA.
SynCity 3000: Bootstrapping Scene-Scale 3D Diffusion
Jul 6, 2026Paul Engstler, Iro Laina, Christian Rupprecht +13D Scene Generation 3D Scene Layout Generation
Visual Geometry Group, University of Oxford
PixWorld: Unifying 3D Scene Generation and Reconstruction in Pixel Space
Jul 6, 2026Sensen Gao, Zhaoqing Wang, Qihang Cao +33D Reconstruction Pixel-Space Diffusion Models
Nanyang Technological University · AISphere
PointDiT: Pixel-Space Diffusion for Monocular Geometry Estimation
Jul 2, 2026Haofei Xu, Rundi Wu, Philipp Henzler +7Diffusion Transformer Monocular 3D Reconstruction
Google · ETH Zurich · University of Tübingen, Tübingen AI Center +3
Rethinking 3D Shape Generation: Diffusion over Superquadrics
Jun 8, 2026Zhiyang Liu, Wanze Li, Yuwei Wu +43D Shape Generation 3D Diffusion Models
Advanced Robotics Centre, National University of Singapore · College of Design and Engineering, National University of Singapore · Engineering Systems and Design, Singapore University of Technology and Design
PatchScene: Patch-based Voxel Diffusion for Large-Scale Scene Completion
Jun 2, 2026Qingdong Xu, Jiajun Zhu, Shilin Zhu +43D Reconstruction Autonomous Driving Perception
1MEGVII Technology · 2Qianli Technology · 4Northeastern University, China +2
Uncertainty-Calibrated Diffusion for Reliable 3D Molecular Graph Generation
Jun 1, 2026Fang Wan, Jingxiang Qu, Yi LiuDiffusion Sampling Molecular Graph Generation
State University of New York at Stony Brook
Structural Energy Guidance for View-Consistent Text-to-3D Generation
May 19, 2026Qing Zhang, Jinguang Tong, Jing Zhang +2Multi-View Consistency Diffusion Model Guidance
Australian National University, Canberra, 2601, ACT, Australia. · CSIRO, Canberra, 2601, ACT, Australia. · The University of Hong Kong, Hong Kong SAR.
Img2CADSeq: Image-to-CAD Generation via Sequence-Based Diffusion
May 13, 2026Shiyu Tan, Zixuan Zhao, Hao Gao +33D Asset Generation Parametric CAD Modeling
School of Software, Tsinghua University, China
Probability-Flow Distillation: Exact Wasserstein Gradient Flow for High-Fidelity 3D Generation
May 9, 2026Rohith Ramanan, A. N. RajagopalanDiffusion Model Distillation Wasserstein Gradient Flows
Department of Physics Indian Institute of Technology Madras · Department of Electrical Engineering Indian Institute of Technology Madras
DVD: Discrete Voxel Diffusion for 3D Generation and Editing
May 8, 2026Zhengrui Xiang, Jiaqi Wu, Fupeng Sun +23D Shape Editing 3D Shape Generation
Imperial College London · Math Magic, Hitem3D · Math Magic
Hyper-DP3: Frequency-Aware Right-Sizing of 3D Diffusion Policies for Visuomotor Control
May 2, 2026Jinhao Zhang, Zhexuan Zhou, Huizhe Li +5Visuomotor Policy Learning Diffusion Policy
Harbin Institute of Technology, Shenzhen · Shanghai Jiao Tong University
InpaintSLat: Inpainting Structured 3D Latents via Initial Noise Optimization
May 1, 2026Jaeyoung Chung, Suyoung Lee, Kyoung Mu LeeLatent Diffusion Models Image Inpainting
Seoul National University, Seoul, South Korea.
Pose-Aware Diffusion for 3D Generation
May 1, 2026Zihan Zhou, Luxi Chen, Jingzhi Zhou +43D Asset Generation 3D Scene Generation
Gaoling School of AI, Renmin University of China · VCIP, School of Computer Science, Nankai University · THU-Bosch MLCenter, Tsinghua University +1
REVIVE 3D: Refinement via Encoded Voluminous Inflated prior for Volume Enhancement
Apr 30, 2026Hankyeol Lee, Wooyeol Baek, Seongdo Kim +13D Asset Generation 3D Diffusion Models
Yonsei University
GenAssets: Generating in-the-wild 3D Assets in Latent Space
Apr 24, 2026Ze Yang, Jingkang Wang, Haowei Zhang +33D Asset Generation Latent Diffusion Models
Waabi · University of Toronto
VS-DDPM: Efficient Low-Cost Diffusion Model for Medical Modality Translation
Apr 24, 2026Nikoo Moradi, Gijs Luijten, Behrus Hinrichs-Puladi +4Image-to-Image Translation 3D Medical Imaging
Institute for Artificial Intelligence in Medicine (IKIM), Essen University Hospital (AöR), University of Duisburg-Essen, Essen, Germany · Institute of Computer Graphics and Vision, Graz University of Technology, Inffeldgasse 16, Graz, 8010, Austria · Center for Virtual and Extended Reality in Medicine (ZvRM), University Hospital Essen (AöR), Essen, Germany +7
Dream-Cubed: Controllable Generative Modeling in Minecraft by Training on Billions of Cubes
Apr 22, 2026Tim Merino, Sam Earle, Ryunosuke Iwai +23D Scene Generation 3D Shape Generation
New York University · Sakana AI
VecSet-Edit: Unleashing Pre-trained LRM for Mesh Editing from Single Image
Feb 4, 2026Teng-Fang Hsiao, Bo-Kai Ruan, Yu-Lun Liu +13D Shape Editing 3D Diffusion Models
National Yang Ming Chiao Tung University, Taiwan
MedForj: An open, large-scale foundational generative prior for high-resolution 3D brain MRI
Oct 29, 2025Samuel W. Remedios, Aaron Carass, Jerry L. Prince +1Flow Matching Healthcare
Image Analysis and Communications Laboratory, Johns Hopkins University · Department of Neurology, Johns Hopkins Hospital

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TCAM-Diff: Triplane-Aware Cross-Attention Medical Diffusion Model

Zhenkai Zhang, Krista A. Ehinger, Tom Drummond

School of Computing and Information Systems, The University of Melbourne · The University of Melbourne

3D Medical Imaging Medical Image Synthesis 3D Representation Learning 3D Diffusion Models

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We introduce TCAM-Diff, a novel 3D medical image generation model that reduces the memory requirements to encode and generate high-resolution 3D data. This model utilizes a decoder-only autoencoder method to learn triplane representation from dense volume and leverages generalization operations to prevent overfitting. Subsequently, it uses a triplane-aware cross-attention diffusion model to learn and integrate these features effectively. Furthermore, the features generated by the diffusion model can be rapidly transformed into 3D volumes using a pre-trained decoder module. Our experiments on three different scales of medical datasets, BrainTumour 128 x 128 x 128, Pancreas 256 x 256 x 256, and Colon 512 x 512 x 512, demonstrate outstanding results. We utilized MSE and SSIM to assess reconstruction quality and leveraged the Wasserstein Generative Adversarial Network (W-GAN) critic to assess generative quality. Comparisons with existing approaches show that our method gives better reconstruction and generation results than other encoder-decoder methods with similar-sized latent spaces.

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