TO-Master is an LLM agent framework that orchestrates finite-element topology optimization from conversational inputs, supporting 2D/3D compliance, thermal, stress-constrained, and multi-load cases while reproducing benchmarks without user code.
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TripoSR: Fast 3D Object Reconstruction from a Single Image
Canonical reference. 78% of citing Pith papers cite this work as background.
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Pith papers citing it
Background
78% of classified citations
abstract
This technical report introduces TripoSR, a 3D reconstruction model leveraging transformer architecture for fast feed-forward 3D generation, producing 3D mesh from a single image in under 0.5 seconds. Building upon the LRM network architecture, TripoSR integrates substantial improvements in data processing, model design, and training techniques. Evaluations on public datasets show that TripoSR exhibits superior performance, both quantitatively and qualitatively, compared to other open-source alternatives. Released under the MIT license, TripoSR is intended to empower researchers, developers, and creatives with the latest advancements in 3D generative AI.
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representative citing papers
Arbor attaches constraint mesh tokens to a frozen text-to-3D denoiser to enable controllable generation obeying hull, avoidance, and touch constraints.
MUSE is a new benchmark and three-stage evaluation protocol for text-to-CAD generation that assesses functionality, manufacturability, and assemblability of B-Rep assemblies beyond geometric similarity.
Img2CADSeq generates standard CAD sequences from images via a multi-stage pipeline with three-level hierarchical codebook encoding, importance-guided compression, and contrastive point-cloud conditioning of a VQ-Diffusion model, outperforming prior methods on new CAD-220K and PrintCAD datasets.
A video generation approach conditions a base model with multi-scale 3D latent features and a cross-attention adapter to produce geometrically realistic and consistent orbital videos from one image.
AniGen directly generates animatable 3D assets with consistent shape, skeleton, and skinning from single images using unified S^3 fields and a two-stage flow-matching pipeline.
ContrAR benchmark reveals that current VLMs show reasonable understanding of contradictory virtual content in AR but need improvement in detection, reasoning, and balancing accuracy with latency.
CARI4D is the first category-agnostic pipeline that produces metric-scale, spatially and temporally consistent 4D reconstructions of human-object interactions from monocular RGB videos via foundation-model hypothesis selection, render-and-compare refinement, and contact reasoning.
SVG360 lifts a single SVG to a view-conditioned representation, uses spatial memory to propagate consistent parts across views, and applies structure-aware vectorization to produce editable multiview SVGs.
SLAT provides a unified 3D latent representation enabling versatile high-quality generation across multiple output formats from text or image inputs.
CORGI reconstructs high-fidelity, animatable 3D dogs from a single in-the-wild image via canonical orbital generation, deformable 3DGS anchored to D-SMAL, and self-supervised generative repair, without 3D supervision.
DualBrep encodes B-rep models as dual scalar fields (SDF geometry + UDF topology) compressed into a shared latent space for flow-matching generation and neural B-rep extraction.
An automated real-to-sim pipeline builds digital twins and affordance-preserving cousins from video, yielding sim evaluations that correlate with real robot policy success and zero-shot sim-to-real gains.
HandMade converts segmented VR strokes into multi-view part guidance and structured prompts so generative 3D models better preserve user-specified spatial scaffolds than text-only or sketch baselines.
Artic-O introduces an end-to-end feed-forward model that reconstructs articulated objects from sparse multi-state images via latent geometry learning and an image-grounded part-reasoning module, outperforming staged methods in speed on PartNet-Mobility while matching accuracy.
φ-Scene performs image-to-3D scene reconstruction via topology-driven physical assembly that resolves penetrations with SDF optimization and settles objects with rigid-body simulation.
A de-biased VLM judge protocol is applied to adapt TRELLIS for single-image furniture 3D generation but yields no improvement over the strong public base across six methods.
A reproducible VLM-judge protocol with position-bias correction is validated as superior to CLIP similarity and geometry-validity proxies for assessing single-image 3D mesh quality.
GeoFlow adds a geometry-consistency reward based on rigid camera flow and object appearance preservation, integrated via reinforcement fine-tuning to improve geometric coherence in video generation.
PanoWorld autoregressively generates consistent multi-room 360-degree panoramas for whole-house VR using a floorplan-derived 3D shell as geometric proxy and a dynamic 3DGS cache for spatial memory.
Sat3DGen improves geometric RMSE from 6.76m to 5.20m and FID from ~40 to 19 for street-level 3D generation from satellite images via geometry-centric constraints and perspective training.
R-DMesh proposes a VAE-based disentanglement of base mesh, motion trajectories, and rectification offset plus Triflow Attention and rectified-flow diffusion to produce 4D meshes aligned to video despite initial pose mismatch.
VISER is a new visually realistic simulation benchmark for robot manipulation tasks that uses PBR materials and MLLM-assisted asset generation, achieving 0.92 Pearson correlation with real-world policy performance.
A generative-AI pipeline dynamically generates and anchors virtual assets to match the shape of physical props, enabling adaptive passive haptics in MR that users rate higher in realism, immersion, and enjoyment than static baselines.
citing papers explorer
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TO-Master: an LLM-agent framework for automated topology optimization
TO-Master is an LLM agent framework that orchestrates finite-element topology optimization from conversational inputs, supporting 2D/3D compliance, thermal, stress-constrained, and multi-load cases while reproducing benchmarks without user code.
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Arbor: Explicit Geometric Conditioning for Controllable 3D Asset Generation
Arbor attaches constraint mesh tokens to a frozen text-to-3D denoiser to enable controllable generation obeying hull, avoidance, and touch constraints.
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MUSE: Benchmarking Manufacturable, Functional, and Assemblable Text-to-CAD Generation
MUSE is a new benchmark and three-stage evaluation protocol for text-to-CAD generation that assesses functionality, manufacturability, and assemblability of B-Rep assemblies beyond geometric similarity.
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Img2CADSeq: Image-to-CAD Generation via Sequence-Based Diffusion
Img2CADSeq generates standard CAD sequences from images via a multi-stage pipeline with three-level hierarchical codebook encoding, importance-guided compression, and contrastive point-cloud conditioning of a VQ-Diffusion model, outperforming prior methods on new CAD-220K and PrintCAD datasets.
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Towards Realistic and Consistent Orbital Video Generation via 3D Foundation Priors
A video generation approach conditions a base model with multi-scale 3D latent features and a cross-attention adapter to produce geometrically realistic and consistent orbital videos from one image.
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AniGen: Unified $S^3$ Fields for Animatable 3D Asset Generation
AniGen directly generates animatable 3D assets with consistent shape, skeleton, and skinning from single images using unified S^3 fields and a two-stage flow-matching pipeline.
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Benchmarking Vision-Language Models under Contradictory Virtual Content Attacks in Augmented Reality
ContrAR benchmark reveals that current VLMs show reasonable understanding of contradictory virtual content in AR but need improvement in detection, reasoning, and balancing accuracy with latency.
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CARI4D: Category Agnostic 4D Reconstruction of Human-Object Interaction
CARI4D is the first category-agnostic pipeline that produces metric-scale, spatially and temporally consistent 4D reconstructions of human-object interactions from monocular RGB videos via foundation-model hypothesis selection, render-and-compare refinement, and contact reasoning.
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SVG360: Editable Multiview Vector Graphics from a Single SVG
SVG360 lifts a single SVG to a view-conditioned representation, uses spatial memory to propagate consistent parts across views, and applies structure-aware vectorization to produce editable multiview SVGs.
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Structured 3D Latents for Scalable and Versatile 3D Generation
SLAT provides a unified 3D latent representation enabling versatile high-quality generation across multiple output formats from text or image inputs.
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CORGI: Consistency-Aware 3D Dog Reconstruction from a Single Image in the Wild
CORGI reconstructs high-fidelity, animatable 3D dogs from a single in-the-wild image via canonical orbital generation, deformable 3DGS anchored to D-SMAL, and self-supervised generative repair, without 3D supervision.
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DualBrep: A Dual-Field Continuous Representation for B-rep Modelling
DualBrep encodes B-rep models as dual scalar fields (SDF geometry + UDF topology) compressed into a shared latent space for flow-matching generation and neural B-rep extraction.
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SimFoundry: Modular and Automated Scene Generation for Policy Learning and Evaluation
An automated real-to-sim pipeline builds digital twins and affordance-preserving cousins from video, yielding sim evaluations that correlate with real robot policy success and zero-shot sim-to-real gains.
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HandMade: Spatial Prompting for Generative 3D Creation with Part-Labeled VR Sketches
HandMade converts segmented VR strokes into multi-view part guidance and structured prompts so generative 3D models better preserve user-specified spatial scaffolds than text-only or sketch baselines.
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Artic-O: End-to-End Articulated Object Reconstruction via Latent Geometry Learning
Artic-O introduces an end-to-end feed-forward model that reconstructs articulated objects from sparse multi-state images via latent geometry learning and an image-grounded part-reasoning module, outperforming staged methods in speed on PartNet-Mobility while matching accuracy.
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$\phi$-Scene: Physically Grounded Image-to-3D Scene Reconstruction
φ-Scene performs image-to-3D scene reconstruction via topology-driven physical assembly that resolves penetrations with SDF optimization and settles objects with rigid-body simulation.
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Judging to Improve: A De-biased VLM-as-3D-Judge Protocol for Single-Image 3D Generation
A de-biased VLM judge protocol is applied to adapt TRELLIS for single-image furniture 3D generation but yields no improvement over the strong public base across six methods.
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A Cross-Model VLM-Judge Protocol for Single-Image 3D Mesh Quality (and Why Cheap Proxies Fall Short)
A reproducible VLM-judge protocol with position-bias correction is validated as superior to CLIP similarity and geometry-validity proxies for assessing single-image 3D mesh quality.
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GeoFlow: Enforcing Implicit Geometric Consistency in Video Generation
GeoFlow adds a geometry-consistency reward based on rigid camera flow and object appearance preservation, integrated via reinforcement fine-tuning to improve geometric coherence in video generation.
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PanoWorld: A Generative Spatial World Model for Consistent Whole-House Panorama Synthesis
PanoWorld autoregressively generates consistent multi-room 360-degree panoramas for whole-house VR using a floorplan-derived 3D shell as geometric proxy and a dynamic 3DGS cache for spatial memory.
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Sat3DGen: Comprehensive Street-Level 3D Scene Generation from Single Satellite Image
Sat3DGen improves geometric RMSE from 6.76m to 5.20m and FID from ~40 to 19 for street-level 3D generation from satellite images via geometry-centric constraints and perspective training.
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R-DMesh: Video-Guided 3D Animation via Rectified Dynamic Mesh Flow
R-DMesh proposes a VAE-based disentanglement of base mesh, motion trajectories, and rectification offset plus Triflow Attention and rectified-flow diffusion to produce 4D meshes aligned to video despite initial pose mismatch.
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Toward Visually Realistic Simulation: A Benchmark for Evaluating Robot Manipulation in Simulation
VISER is a new visually realistic simulation benchmark for robot manipulation tasks that uses PBR materials and MLLM-assisted asset generation, achieving 0.92 Pearson correlation with real-world policy performance.
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Prop-Chromeleon: Adaptive Haptic Props in Mixed Reality through Generative Artificial Intelligence
A generative-AI pipeline dynamically generates and anchors virtual assets to match the shape of physical props, enabling adaptive passive haptics in MR that users rate higher in realism, immersion, and enjoyment than static baselines.
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Feed-Forward 3D Scene Modeling: A Problem-Driven Perspective
The paper proposes a problem-driven taxonomy for feed-forward 3D scene modeling that groups methods by five core challenges: feature enhancement, geometry awareness, model efficiency, augmentation strategies, and temporal-aware modeling.
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Lyra 2.0: Explorable Generative 3D Worlds
Lyra 2.0 produces persistent 3D-consistent video sequences for large explorable worlds by using per-frame geometry for information routing and self-augmented training to correct temporal drift.
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A Semi-Automated Framework for 3D Reconstruction of Medieval Manuscript Miniatures
A pipeline using SAM segmentation and Hi3DGen mesh generation, evaluated on 69 medieval figures, produces usable 3D models for XR and tactile applications with Hi3DGen as the best starting point.
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TripoSG: High-Fidelity 3D Shape Synthesis using Large-Scale Rectified Flow Models
TripoSG generates high-fidelity 3D meshes from input images via a large-scale rectified flow transformer and hybrid-trained 3D VAE on a custom 2-million-sample dataset, claiming state-of-the-art fidelity and generalization.
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InstantMesh: Efficient 3D Mesh Generation from a Single Image with Sparse-view Large Reconstruction Models
InstantMesh produces diverse, high-quality 3D meshes from single images in seconds by combining a multi-view diffusion model with a sparse-view large reconstruction model and optimizing directly on meshes.
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DreamCharacter-1: From 3D Generative Foundation Models to Product-Ready Character Generation
A post-adaptation pipeline on 3D foundation models yields higher-fidelity, faster, animation-ready single-image 3D characters than prior open methods on reported benchmarks.
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Robust 3D Alignment of Generative Reconstructions via Partial Monocular Observations
Training-free Sim(3) alignment method with hallucination filtering for generative 3D to partial monocular registration, plus new GenPMOAlign benchmark showing outperformance over classical and learning baselines.
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Vitality-Aware Compression for Efficient Image-to-Shape Diffusion Transformers
Introduces vitality-aware compression for image-to-3D DiT models via structured pruning, adaptive quantization, and fine-tuning, claiming 66% size reduction with comparable fidelity.
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Sat2City v2: Native 3D City Asset Generation from a Single Satellite Image
Sat2City v2 adapts a pretrained native 3D latent model to generate controllable textured 3D city assets from satellite images via geometry flow fine-tuning and anchored texturing on a collected real dataset.
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GraspFoM: Towards Reconstruction-Driven Robotic Grasping with 3D Foundation Priors
GraspFoM creates a shared 3D latent from SAM3D priors, adds an anchor-initialized diffuser for multimodal grasps, and uses reconstruction-aware scoring plus residual updates to jointly achieve SOTA reconstruction and grasping with few extra parameters.
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AssetGen: Deployable 3D Asset Generation at Interactive Speed
AssetGen is a system that produces deployable 3D assets including meshes, baked normals, and textures from a single reference image in under 30 seconds via a coarse-to-refine VecSet pipeline and co-designed optimizations.
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From Visual Synthesis to Interactive Worlds: Toward Production-Ready 3D Asset Generation
The paper surveys 3D asset generation methods and organizes them around the full production pipeline to assess which outputs meet engine-level requirements for interactive applications.
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AmaraSpatial-10K: A Spatially and Semantically Aligned 3D Dataset for Spatial Computing and Embodied AI
AmaraSpatial-10K supplies 10K deployment-ready 3D assets with metric scaling and metadata, delivering 3.4x higher CLIP Recall@5 than Objaverse and 99.1% physics stability in Habitat-Sim.
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UniMesh: Unifying 3D Mesh Understanding and Generation
UniMesh unifies 3D mesh generation and understanding in one model via a Mesh Head interface, Chain of Mesh iterative editing, and an Actor-Evaluator self-reflection loop.
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FUNCanon: Learning Pose-Aware Action Primitives via Functional Object Canonicalization for Generalizable Robotic Manipulation
FunCanon introduces functional object canonicalization with VLM affordances to create pose-aware action primitives for generalizable imitation learning in robotic manipulation.
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Home3D 1.0: A High-Fidelity Image-to-3D Asset Generation System for Interior Design
Home3D 1.0 describes a four-module image-to-3D system using latent SDF, flow-matching, texture fields, material retrieval, and part-specific VAEs to produce meshes with PBR materials and decomposable components.
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OpenWorldLib: A Unified Codebase and Definition of Advanced World Models
OpenWorldLib defines world models as perception-centered systems with interaction and long-term memory, and provides a modular inference codebase unifying interactive video, 3D, reasoning, and VLA tasks.
- Stream3D: Sequential Multi-View 3D Generation via Evidential Memory