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Found 20 papers, 10 papers with code
IEBins: Iterative Elastic Bins for Monocular Depth Estimation
To alleviate the possible error accumulation during the iterative process, we utilize a novel elastic target bin to replace the original target bin, the width of which is adjusted elastically based on the depth uncertainty.
Ranked #12 on
Monocular Depth Estimation
on KITTI Eigen split
NDDepth: Normal-Distance Assisted Monocular Depth Estimation
Meanwhile, the normal and distance are regularized by a developed plane-aware consistency constraint.
Ranked #12 on
Monocular Depth Estimation
on KITTI Eigen split
Online Unsupervised Video Object Segmentation via Contrastive Motion Clustering
Online unsupervised video object segmentation (UVOS) uses the previous frames as its input to automatically separate the primary object(s) from a streaming video without using any further manual annotation.
ALIKED: A Lighter Keypoint and Descriptor Extraction Network via Deformable Transformation
Image keypoints and descriptors play a crucial role in many visual measurement tasks.
Image Enhancement for Remote Photoplethysmography in a Low-Light Environment
Using collected dataset, we found 1) face detection algorithm cannot detect faces in video captured in low light conditions; 2) A decrease in the amplitude of the pulsatile signal will lead to the noise signal to be in the dominant position; and 3) the chrominance-based method suffers from the limitation in the assumption about skin-tone will not hold, and Green and ICA method receive less influence than POS in dark illuminance environment.
Self-Supervised Monocular Depth Estimation with Self-Reference Distillation and Disparity Offset Refinement
In this work, we propose two novel ideas to improve self-supervised monocular depth estimation: 1) self-reference distillation and 2) disparity offset refinement.
Real-time Local Feature with Global Visual Information Enhancement
Local feature provides compact and invariant image representation for various visual tasks.
Weighted combination and singular spectrum analysis based remote photoplethysmography pulse extraction in low-light environments
The test results verify that the proposed method has stronger robustness to low illumination than state-of-the-art methods, effectively improving the signal-to-noise ratio and heart rate estimation precision.
SMUDLP: Self-Teaching Multi-Frame Unsupervised Endoscopic Depth Estimation with Learnable Patchmatch
Unsupervised monocular trained depth estimation models make use of adjacent frames as a supervisory signal during the training phase.
Implicit Motion-Compensated Network for Unsupervised Video Object Segmentation
Unsupervised video object segmentation (UVOS) aims at automatically separating the primary foreground object(s) from the background in a video sequence.
Sparse LiDAR Assisted Self-supervised Stereo Disparity Estimation
Deep stereo matching has made significant progress in recent years.
DSRGAN: Detail Prior-Assisted Perceptual Single Image Super-Resolution via Generative Adversarial Networks
The proposed method, named DSRGAN, includes a well designed detail extraction algorithm to capture the most important high frequency information from images.
Self-Supervised Monocular Depth and Ego-Motion Estimation in Endoscopy: Appearance Flow to the Rescue
Recently, self-supervised learning technology has been applied to calculate depth and ego-motion from monocular videos, achieving remarkable performance in autonomous driving scenarios.
ALIKE: Accurate and Lightweight Keypoint Detection and Descriptor Extraction
The reprojection loss is then proposed to directly optimize these sub-pixel keypoints, and the dispersity peak loss is presented for accurate keypoints regularization.
FAMINet: Learning Real-time Semi-supervised Video Object Segmentation with Steepest Optimized Optical Flow
A FAMINet, which consists of a feature extraction network (F), an appearance network (A), a motion network (M), and an integration network (I), is proposed in this study to address the abovementioned problem.
Probabilistic Spatial Distribution Prior Based Attentional Keypoints Matching Network
Keypoints matching is a pivotal component for many image-relevant applications such as image stitching, visual simultaneous localization and mapping (SLAM), and so on.
Towards Comprehensive Monocular Depth Estimation: Multiple Heads Are Better Than One
In this work, we investigate into the phenomenon and propose to integrate the strengths of multiple weak depth predictor to build a comprehensive and accurate depth predictor, which is critical for many real-world applications, e. g., 3D reconstruction.
Deep Joint Demosaicing and High Dynamic Range Imaging within a Single Shot
For the former challenge, a spatially varying convolution (SVC) is designed to process the Bayer images carried with varying exposures.
Discriminative and Semantic Feature Selection for Place Recognition towards Dynamic Environments
In this paper, we address the challenges of place recognition due to dynamics and confusable patterns by proposing a discriminative and semantic feature selection network, dubbed as DSFeat.
S&CNet: Monocular Depth Completion for Autonomous Systems and 3D Reconstruction
In this paper, a lightweight yet efficient network (S\&CNet) is proposed to obtain a good trade-off between efficiency and accuracy for the dense depth completion.
