Search
Search Results
-
Multi-scale inputs and context-aware aggregation network for stereo matching
Despite the significant progress made in deep learning-based stereo matching, the accuracy of these methods significantly decreases when faced with...
-
Semantic-Aligned Matching for Enhanced DETR Convergence and Multi-Scale Feature Fusion
The recently proposed DEtection TRansformer (DETR) has established a fully end-to-end paradigm for object detection. However, DETR suffers from slow...
-
Displacement-Invariant Cost Computation for Stereo Matching
Although deep learning-based methods have dominated stereo matching leaderboards by yielding unprecedented disparity accuracy, their inference time...
-
MS-RAFT+: High Resolution Multi-Scale RAFT
Hierarchical concepts have proven useful in many classical and learning-based optical flow methods regarding both accuracy and robustness. In this...
-
Multi-scale pyramidal hash learning for traditional building facade image retrieval
Retrieving images captured of buildings is a critical need for intelligent urban management and tourism services. The different shooting angles,...
-
Few-Shot Stereo Matching with High Domain Adaptability Based on Adaptive Recursive Network
Deep learning based stereo matching algorithms have been extensively researched in areas such as robot vision and autonomous driving due to their...
-
Supervised biadjacency networks for stereo matching
Convolutional neural network (CNN) based stereo matching methods using cost volume techniques have gained prominence in stereo matching....
-
Multi-object Tracking in Remote Sensing Video Based on Motion and Multi-scale Local Cost Volume
Multi-object tracking (MOT) in remote sensing videos is significant in many application scenarios. That task in ordinary scenarios has been widely...
-
Multi-scale hash encoding based neural geometry representation
Recently, neural implicit function-based representation has attracted more and more attention, and has been widely used to represent surfaces using...
-
Space-efficient computation of parallel approximate string matching
Approximate string matching (ASM) has a number of applications in many disciplines, ranging from information retrieval to gene matching. Conventional...
-
Deep Stereo Matching with Superpixel Based Feature and Cost
Previous stereo methods achieved state-of-the-art performances but are still difficult to handle the well-known edge-fattening issue at depth...
-
Human-object interaction detection based on cascade multi-scale transformer
Human-object interaction (HOI) detection is an advanced computer vision task for detecting the relationship between human and surrounding objects....
-
A robust attribute-aware and real-time multi-target multi-camera tracking system using multi-scale enriched features and hierarchical clustering
Multi-Camera Multi-Target Tracking (MTMCT) has challenges such as viewpoint and pose variations, scale and illumination changes, and occlusion....
-
Matching Theory for Distributed Computation in IoT-Fog-Cloud Systems
This chapter provides a state-of-the-art review regarding matching theory-based distributed computation offloading frameworks for IoT-fog-cloud (IFC)...
-
MEDMCN: a novel multi-modal EfficientDet with multi-scale CapsNet for object detection
Object detection in real-world scenarios with multi-modal inputs is crucial for some safety-critical systems, such as autonomous driving, security...
-
CT-MVSNet: Efficient Multi-view Stereo with Cross-Scale Transformer
Recent deep multi-view stereo (MVS) methods have widely incorporated transformers into cascade network for high-resolution depth estimation,...
-
Multi-scale coupled attention for visual object detection
The application of deep neural network has achieved remarkable success in object detection. However, the network structures should be still evolved...
-
A constraints-based approach using ranking-gradient-similarity multi-block matching algorithm
Many works have been done in stereo vision due to its critical importance to the different uses and various areas of computer vision. Recently, the...
-
MSSD: multi-scale self-distillation for object detection
Knowledge distillation techniques have been widely used in the field of deep learning, usually by extracting valid information from a neural network...
-
Enhanced multi-scale feature progressive network for image Deblurring
This paper tackles the problem of single image motion blur removal. Recently methods have achieved state-of-the-art results owe to multi-scale,...
