datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
CameraBench
📷 CameraBench: Towards Understanding Camera Motions in Any Video
SfMs and VLMs performance on CameraBench: Generative VLMs (evaluated with VQAScore) trail classical SfM/SLAM in pure geometry, yet they outperform discriminative VLMs that rely on CLIPScore/ITMScore and—even better—capture scene‑aware semantic cues missed by SfM
After simple supervised fine‑tuning (SFT) on ≈1,400 extra annotated clips, our 7B Qwen2.5‑VL doubles its AP, outperforming the current best… See the full description on the dataset page: https://huggingface.co/datasets/syCen/CameraBench.vsr_random
VSR: Visual Spatial Reasoning
This is the random set of VSR: Visual Spatial Reasoning (TACL 2023) [paper].
Usage
from datasets import load_dataset
data_files = {"train": "train.jsonl", "dev": "dev.jsonl", "test": "test.jsonl"}
dataset = load_dataset("cambridgeltl/vsr_random", data_files=data_files)
Note that the image files still need to be downloaded separately. See data/ for details.
Go to our github repo for more introductions.
Citation
If you find VSR… See the full description on the dataset page: https://huggingface.co/datasets/cambridgeltl/vsr_random.vsr_zeroshot
VSR: Visual Spatial Reasoning
This is the zero-shot set of VSR: Visual Spatial Reasoning (TACL 2023) [paper].
Usage
from datasets import load_dataset
data_files = {"train": "train.jsonl", "dev": "dev.jsonl", "test": "test.jsonl"}
dataset = load_dataset("cambridgeltl/vsr_zeroshot", data_files=data_files)
Note that the image files still need to be downloaded separately. See data/ for details.
Go to our github repo for more introductions.
Citation
If you find… See the full description on the dataset page: https://huggingface.co/datasets/cambridgeltl/vsr_zeroshot.CameraBench-Pro
CameraBench-Pro
This dataset contains the testing split for the CameraBench-Pro evaluation.
cambench_binary_eval
CameraBench Binary Evaluation Dataset
A balanced VQA dataset for evaluating camera motion understanding in videos.
📊 Dataset Statistics
Total Questions: 384
Unique Videos: 119
Unique Questions: 31
Yes Answers: 192 (50.0%)
No Answers: 192 (50.0%)
Balance Ratio: 1.00
Total Size: 126.16 MB (0.12 GB)
Average Video Size: 1.06 MB
🎯 Task Categories
This dataset covers various camera motion tasks including:
Static: 42 questions
Move In: 29 questions
Pan Left: 24… See the full description on the dataset page: https://huggingface.co/datasets/tuhink/cambench_binary_eval.bghira_pseudo-camera-10k-gemini-2.0-flash-thinking-exp-1219-CustomShareGPT
bghira_pseudo-camera-10k-gemini-2.0-flash-thinking-exp-1219-CustomShareGPT
bghira/pseudo-camera-10k with responses/captions generated with gemini-2.0-flash-thinking-exp-1219.
The format should be similar to that of liuhaotian/LLaVA-Instruct-150K.
Images can be found in the images.zip folder. The zip also contains .txt captions for ease of use in non-VQA tasks.
Generation Details
If BlockedPromptException, StopCandidateException, or InvalidArgument was returned, the… See the full description on the dataset page: https://huggingface.co/datasets/PJMixers-Images/bghira_pseudo-camera-10k-gemini-2.0-flash-thinking-exp-1219-CustomShareGPT.trump-2024-campaign-truthsocial-truths
Overview
This dataset contains posts and interactions from Donald J. Trump's TruthSocial account, primarily focused on his 2024 U.S. Presidential election campaign. Each post entry provides comprehensive details such as the account's metadata, post content, number of replies, shares, likes, as well as media URLs (if available), including videos or images. The data offers a rich resource for analyzing political messaging, engagement metrics, and audience reactions throughout the… See the full description on the dataset page: https://huggingface.co/datasets/muhammetakkurt/trump-2024-campaign-truthsocial-truths.ShareGPT4Video
ShareGPT4Video 4.8M Dataset Card
Dataset details
Dataset type:
ShareGPT4Video Captions 4.8M is a set of GPT4-Vision-powered multi-modal captions data of videos.
It is constructed to enhance modality alignment and fine-grained visual concept perception in Large Video-Language Models (LVLMs) and Text-to-Video Models (T2VMs). This advancement aims to bring LVLMs and T2VMs towards the capabilities of GPT4V and Sora.
sharegpt4video_40k.jsonl is generated by GPT4-Vision… See the full description on the dataset page: https://huggingface.co/datasets/Camellia054/ShareGPT4Video.