arXiv AI
Jul 2
Interact3D: Compositional 3D Generation of Interactive Objects
arXiv:2603. 16085v2 Announce Type: replace-cross Abstract: Recent breakthroughs in 3D generation have enabled the synthesis of high-fidelity individual assets.
HI3D 3.0 (Twinkle3D): Object-specific 3D Asset Generation with High Resolution
Hi3D 3.0, also called Twinkle3D, is an image‑to‑3D generation system that produces watertight triangle meshes at a resolution of 2048³. It improves on previous methods by maintaining high representational precision while fixing surface quality and non‑watertight issues, scaling diffusion generation to 300K geometric tokens, strengthening global shape and local detail in a single stage, and adding a fine‑grained image‑3D cross‑modal interaction to better recover object‑specific structures such as inscriptions. The system outperforms four commercial competitors, recovering 82.1 % of inscribed characters with 98.2 % precision versus 21.7 % recall for the best rival.
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arXiv Computer Vision
Aug 31
Cyc3D: Evaluating Cyclic Structural Stability and Asset Usability in Image-to-3D Generation
Cyc3D is a new benchmark for image‑to‑3D generation that evaluates both Cross‑View Object Consistency and Representation Quality. It introduces a closed‑loop View‑Cycle Structural Consistency protocol to measure geometric, perceptual, and semantic drift across repeated render‑regenerate cycles, and also assesses asset usability through geometric structure, fidelity, mesh discretization, and UV quality. Experiments show that closed‑source models outperform open‑source baselines yet still score below 48 on cycle stability, highlighting a gap between visual plausibility and robust 3D understanding.
arXiv AI
Jun 19
CADBench: A Multimodal Benchmark for AI-Assisted CAD Program Generation
arXiv:2605. 10873v2 Announce Type: replace-cross Abstract: Recovering editable CAD programs from images or 3D observations is central to AI-assisted design, but progress is difficult to measure because existing evaluations are fragmented across datasets, modalities, and metrics.
arXiv AI
Jun 24
Inclusive Interactive Collisions for Multi-View Consistent Compositional 3D Generation
arXiv:2606. 24206v1 Announce Type: cross Abstract: Recent breakthroughs in 3D generation have advanced notably with the development of text-to-image diffusion model.
arXiv AI
Jul 10
LSRM: High-Fidelity Object-Centric Reconstruction via Scaled Context Windows
arXiv:2604. 05182v2 Announce Type: replace-cross Abstract: We introduce the Large Sparse Reconstruction Model to study how scaling transformer context windows affects feed-forward 3D reconstruction.
arXiv AI
Jul 28
DreamCAD: Scaling Multi-modal CAD Generation using Differentiable Parametric Surfaces
arXiv:2603. 05607v2 Announce Type: replace-cross Abstract: Computer-Aided Design (CAD) relies on structured and editable geometric representations, yet existing generative methods are constrained by small annotated datasets with explicit design histories or boundary representation (BRep) labels.
arXiv AI
Sep 1
ObjectSplat: Improving Mesh Fidelity and Interactivity for 3D Scenes via Object-Level Mesh Splatting
arXiv:2608.30423v1 Announce Type: cross Abstract: Splatting-based algorithms reconstruct photorealistic, real-time-renderable, and mesh-exportable 3D scenes from regular images, but they represent a...
arXiv Computer Vision
Sep 16
Unlocking Zero-shot Potential of Semi-dense Image Matching via Gaussian Splatting
arXiv:2511.21265v2 Announce Type: replace Abstract: Learning-based image matching critically depends on large-scale, diverse, and geometrically accurate training data. 3D Gaussian Splatting (3DGS) en...
arXiv AI
Jul 10
DreamCharacter-1: From 3D Generative Foundation Models to Product-Ready Character Generation
arXiv:2607. 07817v1 Announce Type: cross Abstract: We present DreamCharacter-1, a lightweight post-adaptation framework that calibrates pretrained 3D foundation models toward high-fidelity, production-ready 3D character generation.
arXiv Computer Vision
Sep 28
PLSR: Progressive and Localized Super-Resolution of 3D Objects via Localized Latent Voxel Diffusion
arXiv:2609.06436v2 Announce Type: replace Abstract: High-resolution 3D asset generation is vital in various 3D applications. Existing state-of-the-art diffusion-based models remain constrained by fix...
arXiv Computer Vision
Oct 2
MEGA: Object-Level Mesh Extraction from 3D Gaussian Splatting via Spatial Visual Distillation
MEGA is a new framework that extracts object-level, watertight meshes from 3D Gaussian Splatting (3DGS) scenes. It uses a segment-then-mesh approach, leveraging Spatial Visual Distillation (SVD) to sample diverse camera views of each segmented object and train a mesh reconstruction model with photometric supervision. Experiments on popular benchmarks show that MEGA outperforms existing methods in accurately recovering object-level 3D occupancy and supports complex physical interactions by combining high-quality meshes with photorealistic 3DGS rendering.
arXiv Computer Vision
4d ago
Tetris3D: 3D Scene Generation With Objects That Fit Together
arXiv:2610.10539v1 Announce Type: new Abstract: We propose Tetris3D, a generative framework for single-image 3D scene reconstruction that recovers objects which are physically and geometrically coher...