9 citations · 11 across the 6 of their papers we have counts for
3 papers · 1 filter
TMPDiff: Temporal Mixed-Precision for Diffusion Models
Basile Lewandowski, Simon Kurz, Aditya Shankar +3
Diffusion models are the go-to method for Text-to-Image generation, but their iterative denoising processes has high inference latency. Quantization reduces compute time by using l…
SFDDM: Single-fold Distillation for Diffusion models
Chi Hong, Jiyue Huang, Robert Birke +3
While diffusion models effectively generate remarkable synthetic images, a key limitation is the inference inefficiency, requiring numerous sampling steps. To accelerate inference…
Multi-Label Gold Asymmetric Loss Correction with Single-Label Regulators
Cosmin Octavian Pene, Amirmasoud Ghiassi, Taraneh Younesian +2
Multi-label learning is an emerging extension of the multi-class classification where an image contains multiple labels. Not only acquiring a clean and fully labeled dataset in mul…