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A synthetic digital city dataset for robustness and generalisation of depth estimation models
Existing monocular depth estimation driving datasets are limited in the number of images and the diversity of driving conditions. The images of...
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BRNet: Exploring Comprehensive Features for Monocular Depth Estimation
Self-supervised monocular depth estimation has achieved encouraging performance recently. A consensus is that high-resolution inputs often yield...
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Optimize Vision Transformer Architecture via Efficient Attention Modules: A Study on the Monocular Depth Estimation Task
IoT and edge devices, capable of capturing data from their surroundings, are becoming increasingly popular. However, the onboard analysis of the...
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Bayesian cue integration of structure from motion and CNN-based monocular depth estimation for autonomous robot navigation
Monocular depth estimation (MDE) provides information (from a single image) about overall scene layout, and is useful in robotics for autonomous...
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Self-supervised Monocular Trained Depth Estimation Using Triplet Attention and Funnel Activation
Dense depth estimation based on a single image is a basic problem in computer vision and has exciting applications in many robotic tasks. Modelling...
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Single image depth estimation using improved U-Net and edge-guide loss
Monocular depth estimation is regarded as a critical link in context-aware scene comprehension, which typically uses image data from a single point...
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Hierarchical Multi-scale Architecture Search for Self-supervised Monocular Depth Estimation
Self-supervised learning has shown great promising in monocular depth estimation task, using images as the only source of supervision. Most existing...
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SwinFusion: Channel Query-Response Based Feature Fusion for Monocular Depth Estimation
Given a single RGB image, Monocular Depth Estimation (MDE) predicts the depth of each pixel by utilizing both global and local information. Most MDE...
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Hybrid Transformer Based Feature Fusion for Self-Supervised Monocular Depth Estimation
With an unprecedented increase in the number of agents and systems that aim to navigate the real world using visual cues and the rising impetus for...
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SACFormer: Unify Depth Estimation and Completion with Prompt
Monocular depth estimation and depth completion are closely correlated, yet they have long been approached as two distinct and separate tasks. In...
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Spike Transformer: Monocular Depth Estimation for Spiking Camera
Spiking camera is a bio-inspired vision sensor that mimics the sampling mechanism of the primate fovea, which has shown great potential for capturing...
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Self-distilled Feature Aggregation for Self-supervised Monocular Depth Estimation
Self-supervised monocular depth estimation has received much attention recently in computer vision. Most of the existing works in literature...
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Using full-scale feature fusion for self-supervised indoor depth estimation
Monocular depth estimation is a crucial task in computer vision, and self-supervised algorithms are gaining popularity due to their independence from...
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Perceptual Monocular Depth Estimation
Monocular depth estimation (MDE), which is the task of using a single image to predict scene depths, has gained considerable interest, in large part...
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Hand pose estimation based on regression method from monocular RGB cameras for handling occlusion
Hand pose estimation is a significant research topic for various computer vision applications. Nonetheless, reliable and robust pose estimation with...
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UCorr: Wire Detection and Depth Estimation for Autonomous Drones
In the realm of fully autonomous drones, the accurate detection of obstacles is paramount to ensure safe navigation and prevent collisions. Among...
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Multi-view Stereo by Fusing Monocular and a Combination of Depth Representation Methods
The design of plane-sweep deep MVS primarily relies on patch-similarity based matching. However, this approach becomes impractical when dealing with...
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TransIndoor: Transformer Based Self-supervised Indoor Depth Estimation
In various tasks of self-supervised monocular depth estimation, the prevalent norm has been the adoption of a U-shaped network structure, utilizing...
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3D hand pose and shape estimation from monocular RGB via efficient 2D cues
Estimating 3D hand shape from a single-view RGB image is important for many applications. However, the diversity of hand shapes and postures, depth...
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Adaptive Co-teaching for Unsupervised Monocular Depth Estimation
Unsupervised depth estimation using photometric losses suffers from local minimum and training instability. We address this issue by proposing an...