Texture Map-Based Weak Supervision Improves Facial Wrinkle Segmentation Performance

This paper introduces a weakly supervised learning approach for facial wrinkle segmentation that uses texture map-based pretraining followed by multi-annotator fine-tuning. Rather than requiring extensive pixel-level wrinkle annotations, the model first learns from facial texture maps before being refined on

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Nvidia’s CEO defends his moat as AI labs change how they improve their AI models.[1] OpenAI launches free AI training course for teachers.[2] Lockheed Martin teams with Iceye to advance AI-enabled targeting.[3] Samsung unveils AI smart glasses with Google and

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I’ve been working on a project called PKE (Precision Knowledge Editing), an open-source method to improve the safety of LLMs by reducing toxic content generation without impacting their general performance. It works by identifying “toxic hotspots” in the model using

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