πŸ“Š
Qvhighlights 1fps dataset by shaunmarvell
⭐ 59.6
πŸ“Š
Dataset

Qvhighlights 1fps

by shaunmarvell shaunmarvell/qvhighlights-1fps
Free2AITools Nexus Index
59.6
S: Semantic 50

Query-time baseline · scored live at search

A: Authority 61
P: Popularity 50
R: Recency 95
Q: Quality 50
Tech Context
Vital Performance —
Source β†’
Data Integrity 59.6 FNI Score
- Size
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Dataset Information Summary
Entity Passport
Registry ID shaunmarvell/qvhighlights-1fps
Provider huggingface
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Cite this dataset

Academic & Research Attribution

BibTeX 
@misc{hf_dataset_shaunmarvell_qvhighlights_1fps,
  author = {shaunmarvell},
  title = {Qvhighlights 1fps Dataset},
  year = {2026},
  howpublished = {\url{https://huggingface.co/datasets/shaunmarvell/qvhighlights-1fps}},
  note = {Accessed via Free2AITools.}
}
APA Style
shaunmarvell. (2026). Qvhighlights 1fps [Dataset]. Free2AITools. https://huggingface.co/datasets/shaunmarvell/qvhighlights-1fps

πŸ”¬Technical Deep Dive

Full Specifications [+]

βš–οΈ Free2AITools Nexus Index V2.0

Methodology How FNI works
Semantic (S) 50

Query-time baseline · scored live at search

Authority (A) 61
Popularity (P) 50
Recency (R) 95
Quality (Q) 50

πŸ’¬ Index Insight

FNI V2.0 for Qvhighlights 1fps: Authority (A:61), Popularity (P:50), Recency (R:95), Quality (Q:50). Semantic (S) is a query-time baseline scored live at search.

Free2AITools Nexus Index

Data Sources / Provenance

HuggingFace API GitHub Metadata Arxiv Citation DB Methodology
Open data Updated: Live data
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26,948

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Dataset Specification

QVHighlights 1fps β€” Preprocessed Frames

Preprocessed version of the QVHighlights dataset for temporal video grounding. Videos are extracted at 1fps, resized to 384Γ—384 JPEG, ready for training without any video I/O at runtime.

Contents

File Description
annotations_train.jsonl 7445 train annotations
annotations_val.jsonl 1550 val annotations
frames folder Train frames batch 0000–1000
frames_000000_001000.tar Train frames batch 0000–1000
frames_001000_002000.tar Train frames batch 1000–2000
frames_002000_003000.tar Train frames batch 2000–3000
frames_003000_004000.tar Train frames batch 3000–4000
frames_004000_005000.tar Train frames batch 4000–5000
frames_005000_006000.tar Train frames batch 5000–6000
frames_006000_007241.tar Train frames batch 6000–7241
frames_007242_007445.tar Remaining train frames
val_frames_000000_end.tar All val frames
cache_embeddings.tar embedings (siglips2-400m) of all the videos

All tars extract to frames/{vid}/{timestamp:08.3f}.jpg.

JSONL Format

Each line is one annotation:

json 
{
  "vid": "6IPwMWhdKpg_60.0_210.0",
  "query": "A person is riding a bike.",
  "duration": 150.0,
  "gt_start_sec": 12.0,
  "gt_end_sec": 45.0,
  "n_frames": 150
}

Source

- Annotations: jwnt4/qvhighlights-50frames (https://huggingface.co/datasets/jwnt4/qvhighlights-50frames)
- Videos: ayushsdev/qvhighlights-videos (https://huggingface.co/datasets/

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Source summary: Based on Hugging Face metadata. Not a recommendation.

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πŸ›‘οΈ Dataset Transparency Report

Technical metadata sourced from upstream repositories.

Open Metadata

πŸ†” Identity & Source

id
hf-dataset--shaunmarvell--qvhighlights-1fps
slug
shaunmarvell--qvhighlights-1fps
source
huggingface
author
shaunmarvell
license
tags
size_categories:1k<n<10k, format:json, modality:image, modality:tabular, modality:text, library:datasets, library:pandas, library:polars, library:mlcroissant, region:us

βš™οΈ Technical Specs

architecture
null
params billions
null
context length
null
pipeline tag

πŸ“Š Engagement & Metrics

downloads
26,948
stars
null
forks
null

Data indexed from public sources. Updated daily.