멀티 카메라/뷰 퓨전 관련 글 목록
2000, Jan 01
- 참조 : https://towardsdatascience.com/monocular-birds-eye-view-semantic-segmentation-for-autonomous-driving-ee2f771afb59
- 참조 : https://towardsdatascience.com/monocular-bev-perception-with-transformers-in-autonomous-driving-c41e4a893944
- 참조 : https://towardsdatascience.com/monocular-3d-lane-line-detection-in-autonomous-driving-4d7cdfabf3b6
- 멀티 카메라/뷰 퓨전을 이용한 다양한 어플리케이션 관련 글 목록 입니다.
멀티 카메라 기반 BEV(Bird Eye View) Sementic Segmentation
- Monocular Semantic Occupancy Grid Mapping with Convolutional Variational Encoder-Decoder Networks
- Learning to Look around Objects for Top-View Representations of Outdoor Scenes
- A Sim2Real Deep Learning Approach for the Transformation of Images from Multiple Vehicle-Mounted Cameras to a Semantically Segmented Image in Bird’s Eye View
- MonoLayout (Amodal scene layout from a single image)
- PyrOccNet, Predicting Semantic Map Representations from Images using Pyramid Occupancy Networks)
- Lift, Splat, Shoot (Encoding Images From Arbitrary Camera Rigs by Implicitly Unprojecting to 3D)
- Projecting Your View Attentively (Monocular Road Scene Layout Estimation via Cross-view Transformation)
- Bird’s-Eye-View Panoptic Segmentation Using Monocular Frontal View Images
- BEV-Seg (Bird’s Eye View Semantic Segmentation Using Geometry and Semantic Point Cloud)
멀티 카메라 기반 Feature Fusion 연구
- Vision-Centric BEV Perception (Survey)
- Self-Supervised Surround-View Depth Estimation with Volumetric Feature Fusion
- NVAutoNet, FAST AND ACCURATE 360◦ 3D VISUAL PERCEPTION FOR SELF DRIVING
- Translating Images Into Maps