[D] Paper Explained: V-JEPA: Revisiting Feature Prediction for Learning Visual Representations from Video (Video Analysis)

[https://youtu.be/7UkJPwz\_N\_0](https://youtu.be/7UkJPwz_N_0)

V-JEPA is a method for unsupervised representation learning of video data by using only latent representation prediction as objective function.

OUTLINE:

0:00 - Intro

1:45 - Predictive Feature Principle

8:00 - (Ad) Weights & Biases course on Structured LLM Outputs

9:45 - The original JEPA architecture

27:30 - V-JEPA Concept

33:15 - V-JEPA Architecture

44:30 - Experimental Results

46:30 - Qualitative Evaluation via Decoding

​

Blog: [https://ai.meta.com/blog/v-jepa-yann-lecun-ai-model-video-joint-embedding-predictive-architecture/](https://ai.meta.com/blog/v-jepa-yann-lecun-ai-model-video-joint-embedding-predictive-architecture/)

Paper: [https://ai.meta.com/research/publications/revisiting-feature-prediction-for-learning-visual-representations-from-video/](https://ai.meta.com/research/publications/revisiting-feature-prediction-for-learning-visual-representations-from-video/)

​

Abstract:

This paper explores feature prediction as a stand-alone …

architecture biases concept course data experimental feature function intro jepa llm machinelearning prediction predictive representation representation learning unsupervised video video data v-jepa