arXiv AI July 10, 2026 By Habiba Kausar, Saeed Anwar, Omar Jamal Hammad, Abdul Bais

SwinIFS: Landmark Guided Swin Transformer For Identity Preserving Face Super Resolution

arXiv:2601. 01406v2 Announce Type: replace-cross Abstract: Face super-resolution aims to recover high-quality facial images from severely degraded low-resolution inputs, but remains challenging due to the loss of fine structural details and identity-specific features.

Machine-generated by The Flow from the publisher's headline and feed description — not written or checked by a human. The full article lives at arXiv AI.

arXiv Machine Learning

Jul 14

Reference-Based Face Super-Resolution Using the Spatial Transformer

arXiv:2607. 11025v1 Announce Type: cross Abstract: Face super-resolution is the task of increasing the resolution of an image containing a face thereby adding finer detail.

By Varun Ramesh Jois, Antonella DiLillo, James Storer

llms computer-vision safety

Hugging Face Trending Papers

Jul 13

Reference-Based Face Super-Resolution Using the Spatial Transformer

Face super-resolution is the task of increasing the resolution of an image containing a face thereby adding finer detail. It is a ubiquitous task in many computer vision applications and quite often the user isn't even aware that it is being performed.

llms computer-vision safety

arXiv AI

Jul 7

PLGSA-Transformer: Periocular Landmark-Guided Attention with Occlusion-Adaptive Cosine Thresholding for Cross-Modal Masked and Unmasked Face Recognition

arXiv:2607. 03581v1 Announce Type: cross Abstract: The widespread adoption of facial masks, accelerated by COVID-19 and mandated in security-sensitive settings, has exposed limitations of conventional face recognition systems.

By Dana A Abdullah

llms multimodal

Hugging Face Trending Papers

Sep 15

FAHCD-Net: Frequency-Adaptive Heatmap-Conditional Diffusion Networks for Robust Facial Landmark Detection

Facial Landmark Detection(FLD) is a crucial task in various applications and has achieved significant advancements in recent years. However, current FLD methods still struggle under challenging condit...

diffusion benchmarks

arXiv Computer Vision

Aug 21

Unwarping the Lens: A Physics-Grounded Approach to Video Glasses Removal

arXiv:2608. 20212v1 Announce Type: new Abstract: High-fidelity removal of eyeglasses from video is a major challenge in facial attribute editing, as the underlying facial geometry is often obscured by complex refractive distortions and view-dependent specular reflections.

By Radim Spetlik, David Futschik, Radek Danecek, Feitong Tan, Ziqian Bai, Rohit Pandey, Yinda Zhang

llms diffusion efficiency

arXiv Computer Vision

Sep 1

Fast and Accurate Image Restoration and Generation with Rank Enhanced Linear Attention

arXiv:2505.16157v3 Announce Type: replace Abstract: Transformer-based models have made remarkable progress in image restoration (IR) tasks. However, the quadratic complexity of self-attention in Tran...

By Yuang Ai

llms diffusion computer-vision benchmarks

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Reference-Based Face Super-Resolution Using the Spatial Transformer

Reference-Based Face Super-Resolution Using the Spatial Transformer

PLGSA-Transformer: Periocular Landmark-Guided Attention with Occlusion-Adaptive Cosine Thresholding for Cross-Modal Masked and Unmasked Face Recognition

FAHCD-Net: Frequency-Adaptive Heatmap-Conditional Diffusion Networks for Robust Facial Landmark Detection

Unwarping the Lens: A Physics-Grounded Approach to Video Glasses Removal

Fast and Accurate Image Restoration and Generation with Rank Enhanced Linear Attention