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cs.CV2024
MatchDiffusion: Training-free Generation of Match-cuts
Alejandro Pardo, Fabio Pizzati, Tong Zhang +4
Match-cuts are powerful cinematic tools that create seamless transitions between scenes, delivering strong visual and metaphorical connections. However, crafting match-cuts is a ch…
cs.CV2024
On Pretraining Data Diversity for Self-Supervised Learning
Hasan Abed Al Kader Hammoud, Tuhin Das, Fabio Pizzati +3
We explore the impact of training with more diverse datasets, characterized by the number of unique samples, on the performance of self-supervised learning (SSL) under a fixed comp…
cs.CV2024
SynthCLIP: Are We Ready for a Fully Synthetic CLIP Training?
Hasan Abed Al Kader Hammoud, Hani Itani, Fabio Pizzati +3
We present SynthCLIP, a CLIP model trained on entirely synthetic text-image pairs. Leveraging recent text-to-image (TTI) networks and large language models (LLM), we generate synth…