201 citations · 275 across the 16 of their papers we have counts for
11 papers · 1 filter
UniSER: A Foundation Model for Unified Soft Effects Removal
Jingdong Zhang, Lingzhi Zhang, Qing Liu +12
Digital images are often degraded by soft effects such as lens flare, haze, shadows, and reflections, which reduce aesthetics even though the underlying pixels remain partially vis…
Fine-grained Defocus Blur Control for Generative Image Models
Ayush Shrivastava, Connelly Barnes, Xuaner Zhang +4
Current text-to-image diffusion models excel at generating diverse, high-quality images, yet they struggle to incorporate fine-grained camera metadata such as precise aperture sett…
ZipIR: Latent Pyramid Diffusion Transformer for High-Resolution Image Restoration
Yongsheng Yu, Haitian Zheng, Zhifei Zhang +7
Recent progress in generative models has significantly improved image restoration capabilities, particularly through powerful diffusion models that offer remarkable recovery of sem…
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…
Distilling Diffusion Models into Conditional GANs
Minguk Kang, Richard Zhang, Connelly Barnes +6
We propose a method to distill a complex multistep diffusion model into a single-step conditional GAN student model, dramatically accelerating inference, while preserving image qua…
Modulated Periodic Activations for Generalizable Local Functional Representations
Ishit Mehta, Michaël Gharbi, Connelly Barnes +3
Multi-Layer Perceptrons (MLPs) make powerful functional representations for sampling and reconstruction problems involving low-dimensional signals like images,shapes and light fiel…