This paper proposes an asymmetric adaptive fusion two-stream network (AAFTS-net) for RGB-D human detection.  The experimental results show that AAFTS-net outperforms existing state-of-the-art methods and can maintain stable performance under conditions of frequent occlusion, low illumination and multiple poses.
AAFTS-net
This paper proposes an asymmetric adaptive fusion two-stream network (AAFTS-net) for RGB-D human detection.  The experimental results show that AAFTS-net outperforms existing state-of-the-art methods and can maintain stable performance under conditions of frequent occlusion, low illumination and multiple poses.
AAFTS-net
This paper also introduces a novel RGB-D dataset for human detection called RGBD-human, on which we verify the performance of the proposed algorithm. 
RGBD-human