Skip to page content
SAVRN
Search Plan a project

Independent publisher

Shih-Ying Yeh

KBlueLeaf

Generative Models Feature Extraction Unsupervised Training

Models in Library1
Datasets in Library0
Models on Hugging Face48
Followers419

Compare the published evidence

This profile connects the 1 model and dataset record shown below to their upstream cards and sources. The library counts describe SAVRN's coverage, rather than this publisher's entire output.

Published tasks: Other.

Reported licenses: apache-2.0. Open a record to review its specific license and conditions.

Compare model specifications, source dates, and hardware estimates on the individual records. Publisher identity verification is separate from a model's quality, deployment readiness, or suitability for your work.

Models

Pretrained DiT decoders for TT-VidT (Decoupling the Temporal Axis for Efficient Motion-Centric Video Pretraining, NeurIPS 2026). Paper · Each TT-VidT encoder pretraining run initialises its decoder from one of these; the training code downloads them automatically through DECODERPRETRAINED, e.g. "KBlueLeaf/TTVidT-decoders/pretrainvideoSqknorm". The decoders work in the 32x32x4 latent space of the frozen f8 frame VAE KBlueLeaf/latentmaid-vae and are conditioned on DINOv3 ViT-B/16 features (768-d). - ImageNet decoders reconstruct an ImageNet image from its DINOv3 class token. - Video decoders reconstruct a later video frame from its class token plus, through cross-attention, the spatial…

Open weights apache-2.0