t2v
Datasets
All datasets matching “t2v”Vchitect_T2V_DataVerse
Vchitect-T2V-Dataverse
Vchitect Team1
1Shanghai Artificial Intelligence Laboratory
Paper |
Project Page |
Data Overview
The Vchitect-T2V-Dataverse is the core dataset used to train our text-to-video diffusion model, Vchitect-2.0: Parallel Transformer for Scaling Up Video Diffusion Models.
It comprises 14 million high-quality videos collected from the Internet, each paired with detailed textual… See the full description on the dataset page: https://huggingface.co/datasets/Vchitect/Vchitect_T2V_DataVerse.vbvr-latent-cache-832x832x33f-t2v-only
VBVR Latent Cache (832×832 × 33f, Wan2.2-TI2V-5B VAE + UMT5-XXL)
Pre-encoded latent cache for the
Video-Reason/VBVR-Dataset
geometric / logical reasoning video corpus, prepared for Equilibrium Matching
(EqM) post-training of Wan-AI/Wan2.2-TI2V-5B-Diffusers on AWS Trainium2.
This is a working cache, not a primary dataset. It exists to skip the
~5 s/sample VAE+T5 encode cost during training. The original videos +
prompts live in the upstream VBVR-Dataset repo.
Source →… See the full description on the dataset page: https://huggingface.co/datasets/Central-Cat/vbvr-latent-cache-832x832x33f-t2v-only.Wan2.1-T2V-1.3B_vidprom_81x480x832_40step_5cfg_5.0shift_4tEvalCrafter_T2V_Dataset
EvalCrafter Text-to-Video (ECTV) Dataset 🎥📊
Code · Project Page · Huggingface Leaderboard · Paper@ArXiv · Prompt list
Welcome to the ECTV dataset! This repository contains around 10000 videos generated by various methods using the Prompt list. These videos have been evaluated using the innovative EvalCrafter framework, which assesses generative models across visual, content, and motion qualities using 17 objective metrics and subjective user opinions.
Dataset Details 📚… See the full description on the dataset page: https://huggingface.co/datasets/RaphaelLiu/EvalCrafter_T2V_Dataset.Vchitect_T2V_DataVerse_256p_8fps_wdshttps://huggingface.co/datasets/Vchitect/Vchitect_T2V_DataVerse resampled to 256p. Intended for training https://github.com/NilanEkanayake/TiTok-Video
Wan2.2-T2V-Activations-FP4
