skxdev007/trinetra: Trinetra - Novel Temporal Event Graph Memory for Efficient Video Understanding via Learnable Attention-Guided Shift

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Authors: S Khavin
Cited by: 0

Abstract

Novel Temporal Event Graph Memory for Efficient Video Understanding via Learnable Attention-Guided Shift Trinetra is a proactive video understanding system that processes video once and enables unlimited queries at near-zero cost. Unlike reactive models (Gemini, GPT-4o) that re-process video for every query, Trinetra builds a rich temporal event graph during ingestion and answers from structured text. Trinetra is a advanced, novel lightweight Python library for semantic video understanding with temporal reasoning. It combines vision-language models (CLIP, SmolVLM) with temporal analysis to understand video content at a deep semantic level.

Fields of Study & Subjects

Multimodal Machine Learning Applications Video Analysis and Summarization Human Pose and Action Recognition

Publication details

Journal / source
Zenodo (CERN European Organization for Nuclear Research)
Publication date
3 March 2026
Language
EN