전체 글46 [X:AI] MOFA-Video 논문 리뷰 MOFA-Video: Controllable Image Animation via Generative Motion Field Adaptions in Frozen Image-to-Video Diffusion Model논문 원본 : https://arxiv.org/abs/2405.20222 MOFA-Video: Controllable Image Animation via Generative Motion Field Adaptions in Frozen Image-to-Video Diffusion ModelWe present MOFA-Video, an advanced controllable image animation method that generates video from the given image using.. 2024. 7. 20. [D&A] GAN 논문 리뷰 Generative Adversarial Nets논문 원본 : https://arxiv.org/abs/1406.2661 Generative Adversarial NetworksWe propose a new framework for estimating generative models via an adversarial process, in which we simultaneously train two models: a generative model G that captures the data distribution, and a discriminative model D that estimates the probability thatarxiv.org 1. Abstract & Introduction mi.. 2024. 7. 17. [X:AI] SimCLR 논문 리뷰 A Simple Framework for Contrastive Learning of Visual Representations논문 원본 : https://arxiv.org/abs/2002.05709 A Simple Framework for Contrastive Learning of Visual RepresentationsThis paper presents SimCLR: a simple framework for contrastive learning of visual representations. We simplify recently proposed contrastive self-supervised learning algorithms without requiring specialized architecture.. 2024. 7. 14. [X:AI] Grad-CAM 논문 리뷰 Grad-CAM: Visual Explanations from Deep Networks via Gradient-based Localization 논문 원본 : https://arxiv.org/abs/1610.02391 Grad-CAM: Visual Explanations from Deep Networks via Gradient-based LocalizationWe propose a technique for producing "visual explanations" for decisions from a large class of CNN-based models, making them more transparent. Our approach - Gradient-weighted Class Activation Ma.. 2024. 7. 6. [Stanford cs231n] Lecture 11(Detection&Segmentation) 강의 주제Object DetectionSemantic SegmentationInstance SegmentationR-CNNFast R-CNNFaster R-CNNMask R-CNN강의 영상https://www.youtube.com/watch?v=nDPWywWRIRo&list=PLC1qU-LWwrF64f4QKQT-Vg5Wr4qEE1Zxk&index=11강의 자료https://cs231n.stanford.edu/slides/2017/cs231n_2017_lecture11.pdf 2024. 6. 16. [Stanford cs231n] Lecture 10(Recurrent Neural Networks) 강의 주제RNN, LSTM강의 영상https://www.youtube.com/watch?v=6niqTuYFZLQ&list=PLC1qU-LWwrF64f4QKQT-Vg5Wr4qEE1Zxk&index=10강의 자료https://cs231n.stanford.edu/slides/2017/cs231n_2017_lecture10.pdf 2024. 6. 16. 이전 1 2 3 4 5 6 ··· 8 다음
