6 papers
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…
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…
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…