5 accepted papers
In this paper, we address the problem of small object detection (SOD) by introducing our novel approach - Dynamically Multiplexed Expanded Features Set (DM-EFS) form. Detecting small objects is challenging as they usually suffer from inadequate feature representation. Hence, to address this, we prop…
Shadow removal from a single image is generally still an open problem. Most existing learning-based methods use supervised learning and require a large number of paired images (shadow and corresponding non-shadow images) for training. A recent unsupervised method, Mask-ShadowGAN, addresses this limi…
Most existing nighttime visibility enhancement methods focus on low light. Night images, however, do not only suffer from low light, but also from man-made light effects such as glow, glare, floodlight, etc. Hence, when the existing nighttime visibility enhancement methods are applied to these image…
In dense foggy scenes, existing optical flow methods are erroneous. This is due to the degradation caused by dense fog particles that break the optical flow basic assumptions such as brightness and gradient constancy. To address the problem, we introduce a semi-supervised deep learning technique tha…
We present a joint Structure-Stereo optimization model that is robust for disparity estimation under low-light conditions. Eschewing the traditional denoising approach - which we show to be ineffective for stereo due to its artefacts and the questionable use of the PSNR metric, we propose to instead…