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