arXiv:2004.07003
공식 코드 · Papers with Code
MXR-U-Nets for Real Time Hyperspectral Reconstruction
원문 초록
In recent times, CNNs have made significant contributions to applications in image generation, super-resolution and style transfer. In this paper, we build upon the work of Howard and Gugger, He et al. and Misra, D. and propose a CNN architecture that accurately reconstructs hyperspectral images from their RGB counterparts. We also propose a much shallower version of our best model with a 10% relative memory footprint and 3x faster inference, thus enabling real-time video applications while still experiencing only about a 0.5% decrease in performance.
함께 살펴볼 논문
공통 태그를 근거로 연결했습니다. 실제 인용 관계나 논문의 우수성을 뜻하지 않습니다.
Implicit Inversion turns CLIP into a Decoder
Hita: Holistic Tokenizer for Autoregressive Image Generation
MAMBO: High-Resolution Generative Approach for Mammography Images
Training-Free Identity Preservation in Stylized Image Generation Using Diffusion Models
MFGDiffusion: Mask-Guided Smoke Synthesis for Enhanced Forest Fire Detection
Implementing Adaptations for Vision AutoRegressive Model
토론
이 논문과 연결된 포럼 글이 아직 없습니다.