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Referring Expression Comprehension datasets
archive 2025-07-28
12 datasets carry the task tag "Referring Expression Comprehension" (the task itself: Referring Expression Comprehension), ordered by the archive's paper count. Page 1 of 1: 12 shown of 12. Facet routes are this site's own (the archive records the tag string, not a page).
The archive holds 12,214 dataset rows; 12,172 are listed. 6 are withheld from every listing and count here as vandalised before snapshot (6 with contact-centre spam in the title, 0 with a spam description on a row that has no homepage, no paper and no papers counted; none with more than 1 paper, 0 with a benchmark), listed in withheld.json; 1 listed row carries a vandalised description, withheld on its page. This gate never withholds a row with a homepage or a paper that resolves, and a clean description; the content rules below withhold a row whose name is spam whatever else it carries. The gate is a phrase list: these are the rows it caught, not a claim that the rest is clean. Before that gate, the site's content rules withhold 36 more rows (invite-code, gambling, travel-booking, contact-centre and similar spam in the name or on a row with nothing real behind it); they have no page and are listed in withheld.json.
Filter 51 task tags shown of 3,717, by dataset count; the full filter by modality, task and language is on /datasets
Referring Expression Comprehension datasets 1–12 of 12
The RefCOCO dataset is a referring expression generation (REG) dataset used for tasks related to understanding natural language expressions that refer to specific objects in images.
439 papers · 11 benchmarks
A new large-scale dataset for referring expressions, based on MS-COCO.
46 papers · 2 benchmarks
The Talk2Car dataset finds itself at the intersection of various research domains, promoting the development of cross-disciplinary solutions for improving the state-of-the-art in grounding natural language into visual space.
45 papers · 0 benchmarks
CLEVR-Ref+ is a synthetic diagnostic dataset for referring expression comprehension.
17 papers · 1 benchmark
GRIT (General Robust Image Task Benchmark)
The General Robust Image Task (GRIT) Benchmark is an evaluation-only benchmark for evaluating the performance and robustness of vision systems across multiple image prediction tasks, concepts, and data sources.
16 papers · 5 benchmarks
Description Detection Dataset (D³, /dikju:b/) is an attempt at creating a next-generation object detection dataset.
10 papers · 1 benchmark
ColonINST is a large-scale instruction tuning dataset designed for multimodal analysis in colonoscopy.
8 papers · 0 benchmarks
ColonINST is a large-scale instruction tuning dataset designed for multimodal analysis in colonoscopy.
8 papers · 2 benchmarks
ColonINST is a large-scale instruction tuning dataset designed for multimodal analysis in colonoscopy.
8 papers · 2 benchmarks
A Game Of Sorts is a collaborative image ranking task.
4 papers · 0 benchmarks
VQDv1 (Visual Query Detection v1)
In Visual Query Detection (VQD), a system is given a query (prompt) natural language and an image, and then the system must produce 0 - N boxes that satisfy that query.
2 papers · 0 benchmarks
FineCops-Ref is a dataset for Compositional Referring Expression Comprehension (REC) that rigorously evaluates Vision-Language Models (VLMs) on compositional reasoning and their ability to identify inconsistencies between images and text.
1 paper · 0 benchmarks
Paper counts and descriptions are the archive's, frozen 2025-07-28; no citation counts, no stars, no trending. Sorting by "most cited" or "newest" was a live-site feature the archive does not carry.