Computer Vision37 [2023-2] 김경훈 - Finding Tiny Faces 원본 논문 링크 : https://arxiv.org/abs/1612.04402 Finding Tiny Faces Though tremendous strides have been made in object recognition, one of the remaining open challenges is detecting small objects. We explore three aspects of the problem in the context of finding small faces: the role of scale invariance, image resolution, arxiv.org 0. Introduction 객체 탐지 기술은 컴퓨터 비전과 이미지 처리 분야에서 중요한 위치를 차지하며, 특히 디지털 이미.. 2024. 2. 6. [2023-2] 백승우 - AN IMAGE IS WORTH 16X16 WORDS: TRANSFORMERS FOR IMAGE RECOGNITION AT SCALE An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale While the Transformer architecture has become the de-facto standard for natural language processing tasks, its applications to computer vision remain limited. In vision, attention is either applied in conjunction with convolutional networks, or used to rep arxiv.org 0. Abstract 트랜스포머 아키텍처는 자연어 처리 작업의 사실상의 표준이 되었지만, 컴퓨터 비전.. 2024. 1. 30. [2023-2] 주서영 - EEG2IMAGE: Image Reconstruction from EEG Brain Signals EEG2IMAGE: Image Reconstruction from EEG Brain Signals Reconstructing images using brain signals of imagined visuals may provide an augmented vision to the disabled, leading to the advancement of Brain-Computer Interface (BCI) technology. The recent progress in deep learning has boosted the study area of synth arxiv.org GitHub - prajwalsingh/EEG2Image: EEG2IMAGE: Image Reconstruction from EEG Br.. 2024. 1. 24. [2023-2] 김경훈 - Latent Consistency Models: Synthesizing High-Resolution Images wi 원본 논문 링크 : https://arxiv.org/abs/2310.04378 Latent Consistency Models: Synthesizing High-Resolution Images with Few-Step InferenceLatent Diffusion models (LDMs) have achieved remarkable results in synthesizing high-resolution images. However, the iterative sampling process is computationally intensive and leads to slow generation. Inspired by Consistency Models (song et al.), we proparxiv.org PD.. 2024. 1. 23. 이전 1 ··· 4 5 6 7 8 9 10 다음
