aadarsh99/ConverSeg
ConverSeg: Conversational Image Segmentation ConverSeg is a benchmark for grounding abstract, intent-driven concepts into pixel-accurate masks. Unlike standard referring expression datasets, ConverSeg focuses on physical reasoning, affordances, and safety. Dataset Structure The dataset contains two splits: sam_seeded: 1,194 samples generated via SAM2 + VLM verification. human_annotated: 493 samples with human-drawn masks (initialized from COCO).… See the full description on the dataset page: https://huggingface.co/datasets/aadarsh99/ConverSeg.
| Author / organization | aadarsh99 |
|---|---|
| License (as declared) | cc-by-4.0 |
| Downloads | 152 (as reported by Hugging Face) |
| Likes | 1 |
| Created | 20 January 2026 |
| Last updated at source | 16 February 2026 |
Recent changes
- 16 Oct 2026 Description: ConverSeg: Conversational Image Segmentation ConverSeg is a benchmark for grounding abstract, intent-driven concepts into pixel-accurate masks. Unlike standard referring expression datasets, ConverSeg focuses on physical reasoning, affordan → ConverSeg: Conversational Image Segmentation ConverSeg is a benchmark for grounding abstract, intent-driven concepts into pixel-accurate masks. Unlike standard referring expression datasets, ConverSeg focuses on physical reasoning, affordan
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