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Text · dataset · 2026

WeatherReasonSeg

Listed in Hugging Face Datasets

Description

WeatherReasonSeg WeatherReasonSeg is an ECCV 2026 benchmark for weather-aware reasoning segmentation in visual language models. It is designed to evaluate whether a model can still understand a reasoning query and produce an accurate segmentation mask when visual evidence is degraded by fog, rain, snow, or nighttime conditions. This benchmark contains 44,721 image-query pairs and highlights three key aspects: a controllable synthetic subset for severity-aware robustness… See the full description on the dataset page: huggingface.co/datasets/wanwan1111/WeatherReasonSeg.

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Where it is published

Documentation and papers

Catalogue records · 1

Topics

Stated by source
image segmentation · tabular · text
Provenance · 1 source records, 11 field assertions
SourceKeyLast seenRaw
Hugging Face Datasetswanwan1111/WeatherReasonSeg7 d agoJSON v1
FieldAssertionExtractorEvidence
access_levelsource · Hugging Faceconnector:huggingface@1.0.0/gated
concepts[field].local:field:computer-science-aimapping · Hugging Faceconnector:huggingface@1.0.0
concepts[modality].hf_modality:tabularsource · Hugging Faceconnector:huggingface@1.0.0
concepts[modality].hf_modality:textsource · Hugging Faceconnector:huggingface@1.0.0
concepts[task].hf_task:image-segmentationsource · Hugging Faceconnector:huggingface@1.0.0/tags[task_categories:*]
created_datesource · Hugging Faceconnector:huggingface@1.0.0
descriptionsource · Hugging Faceconnector:huggingface@1.0.0/description
license_textsource · Hugging Faceconnector:huggingface@1.0.0
publication_datesource · Hugging Faceconnector:huggingface@1.0.0
titlesource · Hugging Faceconnector:huggingface@1.0.0/id
updated_datesource · Hugging Faceconnector:huggingface@1.0.0