You Only Landmark Once: Lightweight U-Net Face Super Resolution with YOLO-World Landmark Heatmaps · DeepSignal
You Only Landmark Once: Lightweight U-Net Face Super Resolution with YOLO-World Landmark Heatmaps arXiv cs.CV · Riccardo Carraro, Anna Briotto, Endi Hysa, Marco Fiorucci, Lamberto Ballan 2d ago · · · · A lightweight U-Net architecture achieves high-resolution face reconstruction using YOLO-World landmark heatmaps for supervision.
Key Points Reconstructs 128x128 images from 16x16 inputs. Uses heatmap-guided loss for key facial features. No adversarial training or complex alignment networks. Reader Mode unavailable (could not extract clean content).
arXiv cs.CV · Zhuojin Li, Hsin-Pai Cheng, Hong Cai, Shizhong Han, Fatih Porikli 2d ago CoReDiT: Spatial Coherence-Guided Token Pruning and Reconstruction for Efficient Diffusion Transformers AI Summary
CoReDiT enhances Diffusion Transformers by optimizing token pruning for efficiency and quality.
📰 Read Original Signal Score
Moderate signal — interesting but narrower impact.
Weight Score
Source authority 20% 78
Community heat 20% 0
Technical impact 30%
📰 Read Original arXiv cs.CV · Alvaro Lopez Pellicer, Plamen Angelov, Marwan Bukhari, Yi Li, Eduardo Soares, Jemma Kerns 2d ago ProtoMedAgent: Multimodal Clinical Interpretability via Privacy-Aware Agentic Workflows AI Summary
ProtoMedAgent enhances clinical interpretability by integrating multimodal reporting with privacy-aware workflows.
arXiv cs.CV · Kanghyun Baek, Jaihyun Lew, Chaehun Shin, Jungbeom Lee, Sungroh Yoon 2d ago Diagnosing and Correcting Concept Omission in Multimodal Diffusion Transformers AI Summary
The study addresses concept omission in MM-DiTs by introducing Omission Signal Intervention to enhance image generation.
arXiv cs.CL · Luis Lara, Aristides Milios, Zhi Hao Luo, Aditya Sharma, Ge Ya Luo, Christopher Beckham, Florian Golemo, Christopher Pal 2d ago Generative Floor Plan Design with LLMs via Reinforcement Learning with Verifiable Rewards AI Summary
A new LLM-based approach generates floor plans while adhering to numerical and topological constraints using reinforcement learning.
China bypasses US GPU bans with 1.54-exaflops 'LineShine' supercomputer — CPU-only monster packs 2.4 million Huawei-designed Armv9 cores AI Summary
China's LineShine supercomputer achieves 1.54 exaflops using 2.4 million Armv9 cores, circumventing US GPU restrictions.
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≥75 high · 50–74 medium · <50 low
Why Featured
This advancement in lightweight U-Net for face super-resolution signals a shift towards more efficient AI models, crucial for developers and PMs focusing on real-time applications and investors looking for scalable solutions.
