Multi-Modal27 [2025-1] 임재열 - Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks는 2017년 ICML에서 발표된,모델에 독립적인 meta learning 알고리즘을 제안한 논문입니다. [MAML]https://arxiv.org/abs/1703.03400 Model-Agnostic Meta-Learning for Fast Adaptation of Deep NetworksWe propose an algorithm for meta-learning that is model-agnostic, in the sense that it is compatible with any model trained with gradient descent and applicable to a vari.. 2025. 7. 5. [2025-1] 백승우 - GUI Agent by Script-based Automation 2025. 7. 4. [2025-1] 박지원-You Said That?: Synthesising Talking Faces from Audio 원문) https://arxiv.org/abs/1705.02966 You said that?We present a method for generating a video of a talking face. The method takes as inputs: (i) still images of the target face, and (ii) an audio speech segment; and outputs a video of the target face lip synched with the audio. The method runs in real timearxiv.org 1. INTRODUCTION i) 개요 및 핵심 아이디어: 대상 얼굴의 이미지와 오디오 음성 segment를 input -> 얼굴이 오디오에 맞.. 2025. 5. 20. [2025-1]박제우 - Scaling Language-Image Pre-training via Masking https://arxiv.org/abs/2212.00794 Scaling Language-Image Pre-training via MaskingWe present Fast Language-Image Pre-training (FLIP), a simple and more efficient method for training CLIP. Our method randomly masks out and removes a large portion of image patches during training. Masking allows us to learn from more image-text pairs givearxiv.org https://blog.outta.ai/284 본 논문은 지난번 리뷰했던 자연어 지도 학습 모.. 2025. 5. 17. 이전 1 2 3 4 5 6 7 다음
