10 accepted papers
Underwater images commonly suffer from foreground-background ambiguity, loss of structural details, and severely reduced contrast, which collectively make underwater object detection (UOD) an inherently challenging task. To handle this issue, we present a residual-guided hierarchical calibration net
Recently, learned video compression (LVC) is undergoing a period of rapid development. However, due to absence of large and high-quality high dynamic range (HDR) video training data, LVC on HDR video is still unexplored. In this paper, we are the first to collect a large-scale HDR video benchmark da…
As an important and practical way to obtain high dynamic range (HDR) video HDR video reconstruction from sequences with alternating exposures is still less explored mainly due to the lack of large-scale real-world datasets. Existing methods are mostly trained on synthetic datasets which perform poor…
Image-based single-modality compression learning approaches have demonstrated exceptionally powerful encoding and decoding capabilities in the past few years , but suffer from blur and severe semantics loss at extremely low bitrates. To address this issue, we propose a multimodal machine learning me…
In recent years, many convolutional neural network-based models are designed for JPEG artifacts reduction, and have achieved notable progress. However, few methods are suitable for extreme low-bitrate image compression artifacts reduction. The main challenge is that the highly compressed image loses…
Thriving underwater applications demand efficient extreme compression technology to realize the transmission of underwater images (UWIs) in very narrow underwater bandwidth. However, existing image compression methods achieve inferior performance on UWIs because they do not consider the characterist…
The captured underwater images suffer from color cast and haze effect caused by absorption and scattering. These interdependent phenomena jointly degrade images, resulting in failure of autonomous machines to recognize image contents. Most existing learning-based methods for underwater image enhance
Lossy compression is an indispensable technique in image/video processing, due to its highly desirable ability of reducing the huge data volume. However, lossy compression introduces complex compression artifacts. To reduce these artifacts, post-processing techniques have been extensively studied. I…
Holoscopic imaging is a prospective acquisition and display solution for providing natural and fatigue-free 3D visualization. However, large amount of data is required to represent the 3D holoscopic content. Therefore, efficient coding schemes for this particular type of image are needed. In this pa…
Multi-view video plus depth (MVD) is a 3D video representation. In MVD, the depth map provides the scene distance information and is used to render the virtual view through Depth Image Based Rendering (DIBR) technique. The depth map coding error will induce distortion in the rendered virtual views.…