🧠
Video Depth Anything Large model by AEmotionStudio
⭐ 36.2
🧠
Model

Video Depth Anything Large

by AEmotionStudio aemotionstudio/video-depth-anything-large
Free2AITools Nexus Index
36.2
S: Semantic 50

Query-time baseline · scored live at search

A: Authority 0
P: Popularity 0
R: Recency 71
Q: Quality 50
Tech Context
Vital Performance —
Source β†’

Technical Constraints

Experimental / High Latency
Low FNI signal 36.2 FNI Score
Tiny - Params
- Context
0 Downloads
Commercial APACHE License
Model Information Summary
Entity Passport
Registry ID aemotionstudio/video-depth-anything-large
License Apache-2.0
Provider huggingface
πŸ“œ

Cite this model

Academic & Research Attribution

BibTeX 
@misc{aemotionstudio_video_depth_anything_large,
  author = {AEmotionStudio},
  title = {Video Depth Anything Large Model},
  year = {2026},
  howpublished = {\url{https://huggingface.co/AEmotionStudio/Video-Depth-Anything-Large}},
  note = {Accessed via Free2AITools.}
}
APA Style
AEmotionStudio. (2026). Video Depth Anything Large [Model]. Free2AITools. https://huggingface.co/AEmotionStudio/Video-Depth-Anything-Large

πŸ”¬Technical Deep Dive

Full Specifications [+]

Quick Commands

πŸ€— HF Download
huggingface-cli download aemotionstudio/video-depth-anything-large

βš–οΈ Free2AITools Nexus Index V2.0

Methodology How FNI works
Semantic (S) 50

Query-time baseline · scored live at search

Authority (A) 0
Popularity (P) 0
Recency (R) 71
Quality (Q) 50

πŸ’¬ Index Insight

FNI V2.0 for Video Depth Anything Large: Authority (A:0), Popularity (P:0), Recency (R:71), 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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⚠️ Incomplete Data

Some information about this model is not available. Use with Caution - Verify details from the original source before relying on this data.

View Original Source β†’

πŸ“ Limitations & Considerations

  • β€’ Benchmark scores may vary based on evaluation methodology and hardware configuration.
  • β€’ VRAM requirements are estimates; actual usage depends on quantization and batch size.
  • β€’ FNI scores are relative rankings and may change as new models are added.
πŸ€— Data Source: Hugging Face β†—
πŸ”„ Updated daily

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

πŸ“Š FNI Methodology πŸ“š Knowledge Baseℹ️ Verify with original source

πŸ›‘οΈ Model Transparency Report

Technical metadata sourced from upstream repositories.

Open Metadata

πŸ†” Identity & Source

id
hf-model--aemotionstudio--video-depth-anything-large
slug
aemotionstudio--video-depth-anything-large
source
huggingface
author
AEmotionStudio
license
Apache-2.0
tags
video, depth-estimation, monocular-depth, safetensors, license:apache-2.0, region:us

βš™οΈ Technical Specs

pipeline tag
depth-estimation

πŸ“Š Engagement & Metrics

downloads
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stars
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forks
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Data indexed from public sources. Updated daily.