40 citations · 89 across the 8 of their papers we have counts for
10 papers
MIMONet: Multi-scale Input and Multi-scale Output Network for Salient Object Detection
Zhaojian Yao, Wei Gao, Tiesong Zhao +2
The existing methods for saliency detection task focus on the application of multi-level features, aiming to take advantage of the respective strengths of high- and low-level featu…
Adaptive Depth-converted-Scale Convolution for Self-supervised Monocular Depth Estimation
Yanbo Gao, Huibin Bai, Huasong Zhou +6
Self-supervised monocular depth estimation (MDE) has received increasing interests in the last few years. The objects in the scene, including the object size and relationship among…
LiftFormer: Lifting and Frame Theory Based Monocular Depth Estimation Using Depth and Edge Oriented Subspace Representation
Shuai Li, Huibin Bai, Yanbo Gao +5
Monocular depth estimation (MDE) has attracted increasing interest in the past few years, owing to its important role in 3D vision. MDE is the estimation of a depth map from a mono…
CWRNN-INVR: A Coupled WarpRNN based Implicit Neural Video Representation
Yiyang Li, Yanbo Gao, Shuai Li +5
Implicit Neural Video Representation (INVR) has emerged as a novel approach for video representation and compression, using learnable grids and neural networks. Existing methods fo…
High Efficiency Wiener Filter-based Point Cloud Quality Enhancement for MPEG G-PCC
Yuxuan Wei, Zehan Wang, Tian Guo +3
Point clouds, which directly record the geometry and attributes of scenes or objects by a large number of points, are widely used in various applications such as virtual reality an…
Rate-Distortion Optimized Skip Coding of Region Adaptive Hierarchical Transform Coefficients for MPEG G-PCC
Zehan Wang, Yuxuan Wei, Hui Yuan +2
Three-dimensional (3D) point clouds are becoming more and more popular for representing 3D objects and scenes. Due to limited network bandwidth, efficient compression of 3D point c…
Approximately Invertible Neural Network for Learned Image Compression
Yanbo Gao, Meng Fu, Shuai Li +4
Learned image compression have attracted considerable interests in recent years. It typically comprises an analysis transform, a synthesis transform, quantization and an entropy co…
3DAttGAN: A 3D Attention-based Generative Adversarial Network for Joint Space-Time Video Super-Resolution
Congrui Fu, Hui Yuan, Liquan Shen +2
In many applications, including surveillance, entertainment, and restoration, there is a need to increase both the spatial resolution and the frame rate of a video sequence. The ai…
OMR-NET: a two-stage octave multi-scale residual network for screen content image compression
Shiqi Jiang, Ting Ren, Congrui Fu +2
Screen content (SC) differs from natural scene (NS) with unique characteristics such as noise-free, repetitive patterns, and high contrast. Aiming at addressing the inadequacies of…
Enhancing context models for point cloud geometry compression with context feature residuals and multi-loss
Chang Sun, Hui Yuan, Shuai Li +2
In point cloud geometry compression, context models usually use the one-hot encoding of node occupancy as the label, and the cross-entropy between the one-hot encoding and the prob…