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cs.CV2026

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…

cs.CV2025

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…

cs.CV2025

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…

cs.CV2025

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

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…

cs.CV2024

Structure-Guided Image Completion with Image-level and Object-level Semantic Discriminators

Haitian Zheng, Zhe Lin, Jingwan Lu +8

Structure-guided image completion aims to inpaint a local region of an image according to an input guidance map from users. While such a task enables many practical applications fo…