Showing 2024Show all
2 papers · 1 filter
cs.CV2024
Layer- and Timestep-Adaptive Differentiable Token Compression Ratios for Efficient Diffusion Transformers
Haoran You, Connelly Barnes, Yuqian Zhou +10
Diffusion Transformers (DiTs) have achieved state-of-the-art (SOTA) image generation quality but suffer from high latency and memory inefficiency, making them difficult to deploy o…
cs.CV2024
Removing Distributional Discrepancies in Captions Improves Image-Text Alignment
Yuheng Li, Haotian Liu, Mu Cai +5
In this paper, we introduce a model designed to improve the prediction of image-text alignment, targeting the challenge of compositional understanding in current visual-language mo…