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01jmhessel /newyorker_caption_contest Dataset Card for New Yorker Caption Contest Benchmarks Dataset Summary See capcon.dev for more! Data from: Do Androids Laugh at Electric Sheep? Humor "Understanding" Benchmarks from The New Yorker Caption Contest @inproceedings{hessel2023androids, title={Do Androids Laugh at Electric Sheep? {Humor} ``Understanding'' Benchmarks from {The New Yorker Caption Contest}}, author={Hessel, Jack and Marasovi{\'c}, Ana and Hwang, Jena D. and Lee, Lillian and… See the full description on the dataset page: https://huggingface.co/datasets/jmhessel/newyorker_caption_contest.imageimage-to-text100K<n<1M76 likes25k downloads3y agoHugging Face02quarterturn /danbooru-1024-eq-captioned Danbooru 1024 e/q Captioned Dataset 59,495 high-resolution (1024px) anime-style images from Danbooru's explicit and questionable rated pools. Each image includes comprehensive JSON captions generated via MiniMax-M3 with structured per-character state-of-dress inventories, camera notes, mood palettes, and post-processing detections. Directory Structure danbooru-1024-eq-captioned.parquet <- consolidated metadata manifest originals/ <-… See the full description on the dataset page: https://huggingface.co/datasets/quarterturn/danbooru-1024-eq-captioned.image10K<n<100K6 likes14k downloads1mo agoHugging Face03google-research-datasets /conceptual_captions Dataset Card for Conceptual Captions Dataset Summary Conceptual Captions is a dataset consisting of ~3.3M images annotated with captions. In contrast with the curated style of other image caption annotations, Conceptual Caption images and their raw descriptions are harvested from the web, and therefore represent a wider variety of styles. More precisely, the raw descriptions are harvested from the Alt-text HTML attribute associated with web images. To arrive at the… See the full description on the dataset page: https://huggingface.co/datasets/google-research-datasets/conceptual_captions.imageimage-to-text1M<n<10M111 likes12k downloads2y agoHugging Face04TommyBsk /Embodied-Captioning Embodied Image Captioning – Manually Annotated Test Set Paper: Embodied Image Captioning: Self-supervised Learning Agents for Spatially Coherent Image Descriptions (ICCV 2025)Authors: Tommaso Galliena, Tommaso Apicella, Stefano Rosa, Pietro Morerio, Alessio Del Bue, Lorenzo NataleAffiliations: Italian Institute of Technology (IIT), University of GenoaProject Website: https://hsp-iit.github.io/embodied-captioningCode: https://github.com/hsp-iit/embodied-captioning 📦… See the full description on the dataset page: https://huggingface.co/datasets/TommyBsk/Embodied-Captioning.tabularimage-to-text1K<n<10K0 likes8.8k downloads1y agoHugging Face05laion /conceptual-captions-12m-webdatasetimage10K<n<100K34 likes6.5k downloads5y agoHugging Face06BLIP3o /BLIP3o-Pretrain-Long-Caption BLIP3o Pretrain Long-Caption Dataset This collection contains 27 million images, each paired with a long (~120 token) caption generated by Qwen/Qwen2.5-VL-7B-Instruct. Download from huggingface_hub import snapshot_download snapshot_download( repo_id="BLIP3o/BLIP3o-Pretrain-Long-Caption", repo_type="dataset" ) Load Dataset without Extracting You don’t need to unpack the .tar archives, use WebDataset support in 🤗datasets instead: from datasets import… See the full description on the dataset page: https://huggingface.co/datasets/BLIP3o/BLIP3o-Pretrain-Long-Caption.image10M<n<100M74 likes6.1k downloads1y agoHugging Face07BLIP3o /BLIP3o-Pretrain-Short-Caption BLIP3o Pretrain Short-Caption Dataset This collection contains 5 million images, each paired with a short (~20 token) caption generated by Qwen/Qwen2.5-VL-7B-Instruct. Download from huggingface_hub import snapshot_download snapshot_download( repo_id="BLIP3o/BLIP3o-Pretrain-Short-Caption", repo_type="dataset" ) Load Dataset without Extracting You don’t need to unpack the .tar archives, use WebDataset support in 🤗datasets instead: from datasets import… See the full description on the dataset page: https://huggingface.co/datasets/BLIP3o/BLIP3o-Pretrain-Short-Caption.image1M<n<10M10 likes5.6k downloads1y agoHugging Face08lambda /pokemon-blip-captionsgated Notice of DMCA Takedown Action We have received a DMCA takedown notice from The Pokémon Company International, Inc. In response to this action, we have taken down the dataset. We appreciate your understanding. imagetext-to-imagen<1K314 likes5k downloads3y agoHugging Face09lingamvamshikrishnareddy /ramanv-image-captions-realtext100K<n<1M0 likes5k downloads27d agoHugging Face10lmms-lab-encoder /COCO-Caption Large-scale Multi-modality Models Evaluation Suite Accelerating the development of large-scale multi-modality models (LMMs) with lmms-eval 🏠 Homepage | 📚 Documentation | 🤗 Huggingface Datasets This Dataset This is a formatted version of COCO-Caption-2014-version. It is used in our lmms-eval pipeline to allow for one-click evaluations of large multi-modality models. @misc{lin2015microsoft, title={Microsoft COCO: Common Objects in Context}… See the full description on the dataset page: https://huggingface.co/datasets/lmms-lab-encoder/COCO-Caption.image10K<n<100K15 likes4.3k downloads3y agoHugging Face11jxie /coco_captions Dataset Card for "coco_captions" More Information needed image100K<n<1M18 likes4k downloads3y agoHugging Face12AbstractPhil /conceptual-captions-12m-webdataset-bertstext10M<n<100M1 likes3.9k downloads2mo agoHugging Face13ming030890 /youtube_caption_yue YouTube ASR Caption Dataset (Cantonese) This dataset was built from YouTube videos with manually provided captions in Cantonese. We used SenseVoice to re-transcribe the audio and filtered segments to build a high-quality collection of audio-caption pairs. What’s included Segments where the ASR output is identical to the original caption — likely clean. Segments where differences are only homophones (同音字) or English words — likely ASR mistakes. This combination supports… See the full description on the dataset page: https://huggingface.co/datasets/ming030890/youtube_caption_yue.audio10K<n<100K2 likes3.5k downloads1y agoHugging Face14Ryan-sjtu /ffhq512-captionimage10K<n<100K5 likes3.1k downloads3y agoHugging Face15lmms-lab-encoder /COCO-Caption2017 Large-scale Multi-modality Models Evaluation Suite Accelerating the development of large-scale multi-modality models (LMMs) with lmms-eval 🏠 Homepage | 📚 Documentation | 🤗 Huggingface Datasets This Dataset This is a formatted version of COCO-Caption-2017-version. It is used in our lmms-eval pipeline to allow for one-click evaluations of large multi-modality models. @misc{lin2015microsoft, title={Microsoft COCO: Common Objects in Context}… See the full description on the dataset page: https://huggingface.co/datasets/lmms-lab-encoder/COCO-Caption2017.image10K<n<100K24 likes3.1k downloads3y agoHugging Face16GeroldMeisinger /laion2b-en-a65_cogvlm2-4bit_captions Abstract This dataset contains image captions for the laion2B-en aesthetics>=6.5 image dataset using CogVLM2-4bit with the "laion-pop"-prompt to generate captions which were "likely" used in Stable Diffusion 3 training. From these image captions new synthetic images were generated using stable-diffusion-3-medium (batch-size=8). The synthetic images are best viewed locally by cloning this repo with: git lfs install git clone… See the full description on the dataset page: https://huggingface.co/datasets/GeroldMeisinger/laion2b-en-a65_cogvlm2-4bit_captions.imageimage-classification1K<n<10K6 likes3k downloads2y agoHugging Face17friedrichor /ActivityNet_Captions About ActivityNet Captions contains 20K long-form videos (180s as average length) from YouTube and 100K captions. Most of the videos contain over 3 annotated events. We follow the existing works to concatenate multiple short temporal descriptions into long sentences and evaluate ‘paragraph-to-video’ retrieval on this benchmark. We adopt the official split: Train: 10,009 videos, 10,009 captions (concatenate from 37,421 short captions) Test (Val1): 4,917 videos, 4,917 captions… See the full description on the dataset page: https://huggingface.co/datasets/friedrichor/ActivityNet_Captions.texttext-to-video10K<n<100K15 likes2.4k downloads1y agoHugging Face18Borise /CaptionQA 📌 CaptionQA Benchmark A high-density, taxonomy-grounded benchmark for evaluating image caption quality and the alignment between image information and generated captions 📄 Paper: CaptionQA: Is Your Caption as Useful as the Image Itself? 📦 Evaluation Code: GitHub Repository Sample Usage You can load the dataset using the Hugging Face datasets library: from datasets import load_dataset # Load the entire dataset dataset = load_dataset("Borise/CaptionQA") # Load a… See the full description on the dataset page: https://huggingface.co/datasets/Borise/CaptionQA.imageimage-text-to-textn<1K9 likes2k downloads10mo agoHugging Face19ProGamerGov /synthetic-dataset-1m-dalle3-high-quality-captions Dataset Card for Dalle3 1 Million+ High Quality Captions Alt name: Human Preference Synthetic Dataset Example grids for landscapes, cats, creatures, and fantasy are also available. Description: This dataset comprises of AI-generated images sourced from various websites and individuals, primarily focusing on Dalle 3 content, along with contributions from other AI systems of sufficient quality like Stable Diffusion and Midjourney (MJ v5 and above). As users typically… See the full description on the dataset page: https://huggingface.co/datasets/ProGamerGov/synthetic-dataset-1m-dalle3-high-quality-captions.imagetext-to-image1M<n<10M154 likes1.9k downloads2y agoHugging Face20laion /captioned-ai-music-snippets Dataset Overview A collection of short audio snippets (3–30 seconds) extracted from publicly shared Suno‑generated songs and captioned with Gemini Flash 2.0. Designed specifically to train and evaluate audio captioning models. Source Clips are randomly cut from the songs referenced in the nyuuzyou/suno repository. Captioning All excerpts have been annotated using Gemini Flash 2.0 for high‑quality, human‑readable audio descriptions. License Apache 2.0 audio1M<n<10M15 likes1.9k downloads11mo agoHugging Face21zlab-princeton /i1-captionsi1: A Simple and Fully Open Recipe for Strong Text-to-Image Models Boya Zeng, Tianze Luo, Shu Pu, Jucheng Shen, Taiming Lu, Gabriel Sarch, Zhuang Liu Princeton University [arXiv][code][model][project page] 1. Overview This dataset contains all captions used in our controlled experiments and the final training of the i1 model. Detailed instructions for downloading the corresponding images and matching the image-caption pairs can be found in our codebase. 2.… See the full description on the dataset page: https://huggingface.co/datasets/zlab-princeton/i1-captions.texttext-to-image100M<n<1B23 likes1.8k downloads1mo agoHugging Face22TTS-AGI /majestrino-unified-detailed-captions Majestrino Unified Detailed Captions Filtered subset of laion/majestrino-data containing all samples with unified_detailed_caption. Stats 4,658,407 samples 932 tar files (~1.1 GB each) ~1,017 GB total Format Each tar contains paired .flac + .json files. JSON fields: caption — the unified detailed caption caption_type — always unified_detailed_caption transcription — speech transcription (when available, normalized from multiple source keys) duration — audio… See the full description on the dataset page: https://huggingface.co/datasets/TTS-AGI/majestrino-unified-detailed-captions.audioaudio-classification1M<n<10M3 likes1.8k downloads6mo agoHugging Face23lingamvamshikrishnareddy /ramanv-image-captions-11gatedtext10M<n<100M2 likes1.7k downloads18d agoHugging Face24Felldude /Gradients_Gradients_and_Text_Full_Logic_Captionsimage1K<n<10K2 likes1.5k downloads15d agoHugging Face25limingcv /Captioned_COCOStuffimage100K<n<1M2 likes1.5k downloads3y agoHugging Face26hanlincs /InternVL-SA1B-Caption-WebDatasetThis repo contains the recaptioned SA1B images in webdataset format. The recaptioned prompts are from https://huggingface.co/datasets/OpenGVLab/InternVL-SA-1B-Caption image10M<n<100M1 likes1.4k downloads1y agoHugging Face27yguooo /newyorker_caption_ranking New Yorker Caption Ranking Dataset Dataset Descriptions Homepage: https://nextml.github.io/caption-contest-data/ Repository: https://github.com/yguooo/cartoon-caption-generation Paper: Humor in AI: Massive Scale Crowd-Sourced Preferences and Benchmarks for Cartoon Captioning Point of Contact: yguo@cs.wisc.edu Dataset Summary We present a novel multimodal preference dataset for creative tasks, consisting of over 250 million human ratings on more than 2.2… See the full description on the dataset page: https://huggingface.co/datasets/yguooo/newyorker_caption_ranking.imagetext-generation1M<n<10M6 likes1.4k downloads2y agoHugging Face28ibm-esa-geospatial /Llama3-SSL4EO-S12-v1.1-captions Llama3-SSL4EO-S12-Captions The captions are aligned with the SSL4EO-S12 v1.1 dataset and were automatically generated using the Llama3-LLaVA-Next-8B model. Please find more information regarding the generation and evaluation in the Llama3-MS-CLIP paper. Code: https://github.com/IBM/MS-CLIP Data Structure We provide the captions in two versions: As a single compressed Parquet file per split and as CSV files with 256 captions each that match the Zarr Zip files of the… See the full description on the dataset page: https://huggingface.co/datasets/ibm-esa-geospatial/Llama3-SSL4EO-S12-v1.1-captions.tabularzero-shot-image-classification100K<n<1M5 likes1.4k downloads1y agoHugging Face29Multimodal-Fatima /COCO_captions_train Dataset Card for "COCO_captions_train" More Information needed image100K<n<1M7 likes1.3k downloads4y agoHugging Face30AudioVisual-Caption /ASID-1M ASID-1M: Attribute-Structured and Quality-Verified Audiovisual Instructions [🏠 Homepage] [📖 Arxiv Paper] [🤗 Models & Datasets] [💻 Code] Introduction We introduce ASID-1M, a large-scale audiovisual instruction dataset built to support universal video understanding with fine-grained, controllable supervision. Most existing video-instruction data represents complex audiovisual content as a single, monolithic caption. This often leads to incomplete coverage (missing audio… See the full description on the dataset page: https://huggingface.co/datasets/AudioVisual-Caption/ASID-1M.textimage-text-to-text100K<n<1M85 likes1.3k downloads7mo agoHugging Face

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