AI Paper Atlas

Research map / Vision-language and multimodal / Human and embodied modeling

Scientific domain vision datasets

Builds large-scale datasets for ecological, geological, and agricultural imagery plus physical prediction.

47 accepted papers at ICML, NeurIPS, ICLR, CVPR and AAAI (2016–2026) · an approach in Human and embodied modeling, keyword cluster “computer vision · humans · abstract”

State History Tried Checklist Preprints Who Export

Where it stands

Not enough benchmark data Fewer than four papers report the same benchmark, so there is no record to follow.

20 papers in 2023–24 and 16 in 2025–26 (at ICML, NeurIPS, ICLR, CVPR and AAAI); its share of the topic shrank, from 3.8% to 2.4%.

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: 1172018: 0182019: 0192020: 0202021: 4212022: 5222023: 5232024: 15242025: 12252026: 426

Most cited paper of each year

Earliest papers here

What has been tried

36 papers here report 357 measured changes (a component added, removed or swapped, compared with a baseline): helped 70%, no clear effect 7%, hurt 21%, mixed 3%. Papers mostly publish changes that helped, so "helped" is over-represented.

Ablations in recent papers

What was changedMeasured onResultEffectPaper
Use taxonomic names rather than scientific namesRare Species · Zero-shot accuracy22.3→26.6; 28.0→30.4HelpedBioCLIP: A Vision Foundation Model for the Tree of Life (CVPR 2024 · 124 citations)
Add attention poolingIP102 Classification · Acc@168.9% to 69.5%HelpedInsect-Foundation: A Foundation Model and Large-scale 1M Dataset for Visual Insect Understanding (CVPR 2024 · 18 citations)
Replace direct regression with a QuadTree classifierOSV-5M test · Geoscore+ 720HelpedOpenStreetView-5M: The Many Roads to Global Visual Geolocation (CVPR 2024 · 15 citations)
Add class-balanced re-weighting and focal loss to MaxViT-TFV-Classification · classification performanceHelpedFish-Vista: A Multi-Purpose Dataset for Understanding & Identification of Traits from Images (CVPR 2025 · 12 citations)
Add head direction to UWBBehavior classification OS · average F1.707±.051 -> .707±.064No clear effectMmCows: A Multimodal Dataset for Dairy Cattle Monitoring (NeurIPS 2024 · 12 citations)
add Camera Parameters Estimator (CPE)Vi-Fi · SUM32.12 -> 27.24HelpedOOSTraj: Out-of-Sight Trajectory Prediction With Vision-Positioning Denoising (CVPR 2024 · 10 citations)
add 4D Radar to LiDARVehicle Easy, IoU=0.5 · AP47.23 -> 53.61HelpedV2X-Radar: A Multi-modal Dataset with 4D Radar for Cooperative Perception (NeurIPS 2025 · 7 citations)
add environment-guided area representation learningForecast, real-world data · AUPRC60.2 -> 70.1HelpedSim2Real-Fire: A Multi-modal Simulation Dataset for Forecast and Backtracking of Real-world Forest Fire (NeurIPS 2024 · 4 citations)
Add Attention mechanism onlyEvaluation Area · accuracy92.97 -> 95.41HelpedDCV2I: A Practical Approach for Supporting Geographers’ Visual Interpretation in Dune Segmentation with Deep Vision Models (AAAI 2024 · 3 citations)
Include more examples from the same target class in the prompt (target-class-only rather than at-least-one-target sampling)Nanoparticle shapes (test set; N=4) · average accuracy0.59±0.12 -> 0.66±0.09 (textual); 0.55±0.11 -> 0.62±0.09 (tabular)HelpedUnveiling the Potential of AI for Nanomaterial Morphology Prediction (ICML 2024 · 3 citations)
replace random deduplication with quality-guided deduplicationDataComp (38 downtasks) · Avg. Perf.0.145 -> 0.147HelpedQuality over Quantity: Boosting Data Efficiency Through Ensembled Multimodal Data Curation (AAAI 2025 · 2 citations)
Remove caption augmentationHuman-created test set · CLIPScore26.776 -> 25.703HurtAutomaTikZ: Text-Guided Synthesis of Scientific Vector Graphics with TikZ (ICLR 2024 · 2 citations)

What reviewers will expect

Datasets and baselines named in the 13 papers of this approach from 2025–2026 that have a full-text summary. Leaving out the common ones is a frequent review question.

Baselines

  • MLP · 2 of 13 papers

Recent preprints

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    Who publishes on it

    Institutions on the most papers of this approach since 2023 (of 36 papers; from OpenAlex and the papers' affiliations).

    Use it

    Download BibTeX of 32 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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