EfficientPS: Efficient Panoptic Segmentation (Mission: Impossible - Fallout) 4K 60FPS
Rohit Mohan and Abhinav Valada
EfficientPS: Efficient Panoptic Segmentation
Paper: https://arxiv.org/abs/2004.02307
Demo: https://rl.uni-freiburg.de/research/panoptic
Music: Lorne Balfe
Видео EfficientPS: Efficient Panoptic Segmentation (Mission: Impossible - Fallout) 4K 60FPS канала Robot Learning Freiburg
EfficientPS: Efficient Panoptic Segmentation
Paper: https://arxiv.org/abs/2004.02307
Demo: https://rl.uni-freiburg.de/research/panoptic
Music: Lorne Balfe
Видео EfficientPS: Efficient Panoptic Segmentation (Mission: Impossible - Fallout) 4K 60FPS канала Robot Learning Freiburg
Показать
Комментарии отсутствуют
Информация о видео
Другие видео канала
![EfficientLPS: Efficient LiDAR Panoptic Segmentation](https://i.ytimg.com/vi/_ay7ci-Nd0E/default.jpg)
![Robot Localization in Floor Plans Using a Room Layout Edge Extraction Network](https://i.ytimg.com/vi/BE0myn9yGGI/default.jpg)
![Learning and Aggregating Lane Graphs for Urban Automated Driving](https://i.ytimg.com/vi/fiGWIzbH01o/default.jpg)
![CoDEPS: Continual Learning for Depth Estimation and Panoptic Segmentation](https://i.ytimg.com/vi/4m4swaIkHyg/default.jpg)
![Syn-Mediverse: A Multimodal Synthetic Dataset for Scene Understanding of Healthcare Facilities](https://i.ytimg.com/vi/itAL_z_8kHY/default.jpg)
![Amodal Optical Flow](https://i.ytimg.com/vi/tzeQ0h9ttYM/default.jpg)
![VLocNet++: Deep Multitask Learning for Semantic Visual Localization and Odometry](https://i.ytimg.com/vi/mf1UUhlr-IQ/default.jpg)
![Dynamic Object Removal and Spatio-Temporal RGB-D Inpainting via Geometry-Aware Adversarial Learning](https://i.ytimg.com/vi/jLrcc_-C06E/default.jpg)
![Panoptic Out-of-Distribution Segmentation](https://i.ytimg.com/vi/Jxil0b7GdhM/default.jpg)
![CenterGrasp Teaser](https://i.ytimg.com/vi/ArYQNprFcUQ/default.jpg)
![Continual SLAM: Beyond Lifelong Simultaneous Localization and Mapping through Continual Learning](https://i.ytimg.com/vi/ASEzwnV4vNk/default.jpg)
![Efficient Learning of Urban Driving Policies Using Bird's-Eye-View State Representations (ITSC 2023)](https://i.ytimg.com/vi/Tp1wt0lHaEI/default.jpg)
![MoMa-LLM: Language-Grounded Dynamic Scene Graphs for Interactive Object Search w Mobile Manipulation](https://i.ytimg.com/vi/ijorqhbqiJ0/default.jpg)
![EfficientPS: Efficient Panoptic Segmentation](https://i.ytimg.com/vi/j11mvFqFmfA/default.jpg)
![Unsupervised Domain Adaptation for LiDAR Panoptic Segmentation](https://i.ytimg.com/vi/--XHyAfv4U4/default.jpg)
![FreiDOG ft. Akaishi Daiko Freiburg @ 10th anniversary of kite-mentoring](https://i.ytimg.com/vi/LXnOC4EXCcE/default.jpg)
![BEVCar: Camera-Radar Fusion for BEV Map and Object Segmentation](https://i.ytimg.com/vi/bB_k_6IvPHQ/default.jpg)
![Learning Hierarchical Interactive Multi-Object Searchfor Mobile Manipulation](https://i.ytimg.com/vi/xWKC484sHPE/default.jpg)
![LCDNet: Deep Loop Closure Detection and Point Cloud Registration for LiDAR SLAM](https://i.ytimg.com/vi/nAvTdEFRh_s/default.jpg)
![The AI Driving Olympics (AI-DO): NeurIPS 2021](https://i.ytimg.com/vi/iTGnAhoBPc4/default.jpg)
![Amodal Panoptic Segmentation](https://i.ytimg.com/vi/tPR1ZR2E070/default.jpg)