BidNet: Binocular Image Dehazing Without Explicit Disparity Estimation

CVPR 2020 Yanwei Pang Jing Nie Jin Xie Jungong Han Xuelong Li

Heavy haze results in severe image degradation and thus hampers the performance of visual perception, object detection, etc. On the assumption that dehazed binocular images are superior to the hazy ones for stereo vision tasks such as 3D object detection and according to the fact that image haze is a function of depth, this paper proposes a Binocular image dehazing Network (BidNet) aiming at dehazing both the left and right images of binocular images within the deep learning framework... (read more)

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