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Research map / Image generation / Autoregressive and latent generation

Compositional scene generation

Generate images from scene graphs and compositional structure.

105 accepted papers at ICML, NeurIPS, ICLR, CVPR and AAAI (2016–2026) · an approach in Autoregressive and latent generation, keyword cluster “motion · layout · object”

State History Benchmarks Tried Checklist Preprints Who Export

Where it stands

Quiet None of the tracked benchmarks has a report from 2025–26.

35 papers in 2023–24 and 36 in 2025–26 (at ICML, NeurIPS, ICLR, CVPR and AAAI); its share of the topic shrank, from 7.4% to 4.0%.

No longer reported by papers here: COCO-Stuff (FID, last in 2024); Visual Genome (FID, last in 2024).

How this is decided

A benchmark is tracked when at least four papers of this approach report their own method on the same dataset and metric in at least two different years. Its record is the best number reported up to 2024 compared with the best reported in 2025–26: still improving means at least 1% better, flat means at most 0.2% better with at least two papers from 2025–26 trying. Numbers on a different scale from the rest (a fraction among percentages) and far outliers are left out. Results come from different papers with different setups, so they are signals, not head-to-head comparisons. The share of papers is counted at ICML, NeurIPS, ICLR, CVPR and AAAI.

How it got here

2016: 1162017: 3172018: 5182019: 5192020: 4202021: 4212022: 12222023: 15232024: 20242025: 20252026: 1626

Most cited paper of each year

Earliest papers here

Benchmark records

The best number each year that beat every earlier one, among papers of this approach reporting their own method. Numbers are extracted by AI from each paper's text; check the paper before citing.

COCO-Stuff · FID (lower is better)

6 papers, 2019–2024 · not reported since 2024

2019: 38.292020: 28.82022: 22.15
20192024
YearBest so farSet by
201938.29PasteGAN: A Semi-Parametric Method to Generate Image from Scene Graph (NeurIPS 2019 · 60 citations)
202028.8Panoptic-Based Image Synthesis (CVPR 2020 · 46 citations)
202222.15Modeling Image Composition for Complex Scene Generation (CVPR 2022 · 39 citations)

Visual Genome · FID (lower is better)

4 papers, 2019–2024 · not reported since 2024

2019: 35.252022: 17.74
20192024
YearBest so farSet by
201935.25PasteGAN: A Semi-Parametric Method to Generate Image from Scene Graph (NeurIPS 2019 · 60 citations)
202217.74Modeling Image Composition for Complex Scene Generation (CVPR 2022 · 39 citations)

What has been tried

86 papers here report 873 measured changes (a component added, removed or swapped, compared with a baseline): helped 77%, no clear effect 3%, hurt 18%, mixed 2%. Papers mostly publish changes that helped, so "helped" is over-represented.

Ablations in recent papers

What was changedMeasured onResultEffectPaper
Add stitched-image mask conditionDIR-D test set · SSIM0.6125 -> 0.7337HelpedRecDiffusion: Rectangling for Image Stitching with Diffusion Models (CVPR 2024 · 25 citations)
add point resampling to balance point-cloud densityHoliCity · FID131.38 -> 71.98HelpedSat2Scene: 3D Urban Scene Generation from Satellite Images with Diffusion (CVPR 2024 · 21 citations)
add heatmap condition cj by concatenating it with image latent z03DPW · MPJPE87.6 -> 75.1HelpedDPMesh: Exploiting Diffusion Prior for Occluded Human Mesh Recovery (CVPR 2024 · 17 citations)
replace GCN with SGFormerCOCO-Stuff · IS16.5 -> 17.5HelpedR3CD: Scene Graph to Image Generation with Relation-Aware Compositional Contrastive Control Diffusion (AAAI 2024 · 15 citations)
Add DRSE to the baselineStructured3D test, FOV 90° · FID39.450 -> 38.805HelpedSphereDiffusion: Spherical Geometry-Aware Distortion Resilient Diffusion Model (AAAI 2024 · 15 citations)
Add Low-Fidelity SelectionMVTec AD generated defects · KID28.485 → 25.947HelpedDefectFill: Realistic Defect Generation with Inpainting Diffusion Model for Visual Inspection (CVPR 2025 · 14 citations)
Add weighted noise lossDESOBAv2 BOS test images · global RMSE8.285 -> 7.041HelpedShadow Generation for Composite Image Using Diffusion Model (CVPR 2024 · 14 citations)
Add FAG, semantic edges, and spatial edges to the Transformer baselineUGCrop5K · averaged ACC554.3 -> 60.8HelpedSpatial-Semantic Collaborative Cropping for User Generated Content (AAAI 2024 · 12 citations)
add the LDR environment mapRelighting ablation benchmark · PSNR25.503 -> 26.052HelpedNeural Gaffer: Relighting Any Object via Diffusion (NeurIPS 2024 · 12 citations)
Add the tiling constraintSelf-tiling · TS0.28 -> 0.03HelpedTiled Diffusion (CVPR 2025 · 9 citations)
add PGIHuman-Art · AP (%)39.52 -> 47.80HelpedGRPose: Learning Graph Relations for Human Image Generation with Pose Priors (AAAI 2025 · 6 citations)
add 2D UV layout information to point cloud guidanceGarment texture synthesis · FID187.63 -> 96.97HelpedTexGarment: Consistent Garment UV Texture Generation via Efficient 3D Structure-Guided Diffusion Transformer (CVPR 2025 · 6 citations)

What reviewers will expect

Datasets and baselines named in the 21 papers of this approach from 2025–2026 that have a full-text summary. Leaving out the common ones is a frequent review question.

Datasets

  • COCO · 2 of 21 papers

Baselines

  • LAMA · 2 of 21 papers
  • PowerPaint · 2 of 21 papers
  • Uni-ControlNet · 2 of 21 papers
  • Stable Diffusion · 2 of 21 papers
  • DINOSAUR · 2 of 21 papers
  • Slot Attention · 2 of 21 papers
  • InstructPix2Pix · 2 of 21 papers

Recent preprints

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    Who publishes on it

    Institutions on the most papers of this approach since 2023 (of 71 papers; from OpenAlex and the papers' affiliations).

    Use it

    Download BibTeX of 40 key papersOpen the topic in the interactive map

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    Same keyword cluster

    Elsewhere in the topic

    Benchmark numbers, ablations and baseline numbers are extracted by AI from each paper's full text and can be wrong; the paper is the authority. Data: results index of 2026-11-02, citation counts from OpenAlex (2026-10-09).

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