  The display devices like HDR10 televisions are increasingly prevalent in our
daily life for visualizing high dynamic range (HDR) images. But the majority of
media images on the internet remain in 8-bit standard dynamic range (SDR)
format. Therefore, converting SDR images to HDR ones by inverse tone mapping
(ITM) is crucial to unlock the full potential of abundant media images.
However, existing ITM methods are usually developed with complex network
architectures requiring huge computational costs. In this paper, we propose a
lightweight Improved Residual Network (IRNet) by enhancing the power of popular
residual block for efficient ITM. Specifically, we propose a new Improved
Residual Block (IRB) to extract and fuse multi-layer features for fine-grained
HDR image reconstruction. Experiments on three benchmark datasets demonstrate
that our IRNet achieves state-of-the-art performance on both the ITM and joint
SR-ITM tasks. The code, models and data will be publicly available at
https://github.com/ThisisVikki/ITM-baseline.
