Search Results for author: Allan Raventos

Found 4 papers, 2 papers with code

Learning to Fuse Things and Stuff

no code implementations4 Dec 2018 Jie Li, Allan Raventos, Arjun Bhargava, Takaaki Tagawa, Adrien Gaidon

We propose an end-to-end learning approach for panoptic segmentation, a novel task unifying instance (things) and semantic (stuff) segmentation.

Ranked #26 on Panoptic Segmentation on Cityscapes val (using extra training data)

Instance Segmentation Panoptic Segmentation +1

Real-Time Panoptic Segmentation from Dense Detections

no code implementations CVPR 2020 Rui Hou, Jie Li, Arjun Bhargava, Allan Raventos, Vitor Guizilini, Chao Fang, Jerome Lynch, Adrien Gaidon

Panoptic segmentation is a complex full scene parsing task requiring simultaneous instance and semantic segmentation at high resolution.

Clustering object-detection +4

Reinforcement Learning based Control of Imitative Policies for Near-Accident Driving

1 code implementation1 Jul 2020 Zhangjie Cao, Erdem Biyik, Woodrow Z. Wang, Allan Raventos, Adrien Gaidon, Guy Rosman, Dorsa Sadigh

To address driving in near-accident scenarios, we propose a hierarchical reinforcement and imitation learning (H-ReIL) approach that consists of low-level policies learned by IL for discrete driving modes, and a high-level policy learned by RL that switches between different driving modes.

Autonomous Driving Imitation Learning +2

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