arXiv:1908.01499
GAN Path Finder: Preliminary results
원문 초록
2D path planning in static environment is a well-known problem and one of the common ways to solve it is to 1) represent the environment as a grid and 2) perform a heuristic search for a path on it. At the same time 2D grid resembles much a digital image, thus an appealing idea comes to being -- to treat the problem as an image generation task and to solve it utilizing the recent advances in deep learning. In this work we make an attempt to apply a generative neural network as a path finder and report preliminary results, convincing enough to claim that this direction of research is worth further exploration.
함께 살펴볼 논문
공통 태그를 근거로 연결했습니다. 실제 인용 관계나 논문의 우수성을 뜻하지 않습니다.
MFGDiffusion: Mask-Guided Smoke Synthesis for Enhanced Forest Fire Detection
Implementing Adaptations for Vision AutoRegressive Model
CharaConsist: Fine-Grained Consistent Character Generation
MGVQ: Could VQ-VAE Beat VAE? A Generalizable Tokenizer with Multi-group Quantization
NeoBabel: A Multilingual Open Tower for Visual Generation
Estimating Object Physical Properties from RGB-D Vision and Depth Robot Sensors Using Deep Learning
토론
이 논문과 연결된 포럼 글이 아직 없습니다.