6 citations · 7 across the 11 of their papers we have counts for
6 papers · 1 filter
The GEST-Engine: From Event Graphs to Synthetic Video. A Full Technical Report
Nicolae Cudlenco, Mihai Masala, Marius Leordeanu
We present the GEST-Engine, a complete system that goes from natural-language text to fully-annotated multi-actor video. At its core is an explicit world model: rather than encodin…
GTASA: Ground Truth Annotations for Spatiotemporal Analysis, Evaluation and Training of Video Models
Nicolae Cudlenco, Mihai Masala, Marius Leordeanu
Game engines hold what video models struggle to learn: a complete, explicit world state behind every frame. We turn one into a data instrument. GEST-Engine, our production-grade op…
Authoring for Living Worlds: Tool-Constrained LLM Agents for Executable Multi-Actor Scenarios
Nicolae Cudlenco, Mihai Masala, Marius Leordeanu
Authoring a multi-actor scenario for a living 3D world, where every action changes its state, and each action's validity depends on the state accumulated before it, demands the fre…
From Vision To Language through Graph of Events in Space and Time: An Explainable Self-supervised Approach
Mihai Masala, Marius Leordeanu
The task of describing video content in natural language is commonly referred to as video captioning. Unlike conventional video captions, which are typically brief and widely avail…
Learning from Random Subspace Exploration: Generalized Test-Time Augmentation with Self-supervised Distillation
Andrei Jelea, Ahmed Nabil Belbachir, Marius Leordeanu
We introduce Generalized Test-Time Augmentation (GTTA), a highly effective method for improving the performance of a trained model, which unlike other existing Test-Time Augmentati…
Towards Zero-Shot & Explainable Video Description by Reasoning over Graphs of Events in Space and Time
Mihai Masala, Marius Leordeanu
In the current era of Machine Learning, Transformers have become the de facto approach across a variety of domains, such as computer vision and natural language processing. Transfo…