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Counting Cows: Tracking Illegal Cattle Ranching From High-Resolution Satellite Imagery
Cattle farming is responsible for 8.8% of greenhouse gas emissions world...
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Affinity LCFCN: Learning to Segment Fish with Weak Supervision
Aquaculture industries rely on the availability of accurate fish body me...
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Synbols: Probing Learning Algorithms with Synthetic Datasets
Progress in the field of machine learning has been fueled by the introdu...
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CVPR 2020 Continual Learning in Computer Vision Competition: Approaches, Results, Current Challenges and Future Directions
In the last few years, we have witnessed a renewed and fast-growing inte...
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A Realistic Fish-Habitat Dataset to Evaluate Algorithms for Underwater Visual Analysis
Visual analysis of complex fish habitats is an important step towards su...
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A Weakly Supervised Consistency-based Learning Method for COVID-19 Segmentation in CT Images
Acquiring count annotations generally requires less human effort than po...
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LOOC: Localize Overlapping Objects with Count Supervision
Acquiring count annotations generally requires less human effort than po...
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Learning Data Augmentation with Online Bilevel Optimization for Image Classification
Data augmentation is a key practice in machine learning for improving ge...
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Pix2Shape – Towards Unsupervised Learning of 3D Scenes from Images using a View-based Representation
We infer and generate three-dimensional (3D) scene information from a si...
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Online Fast Adaptation and Knowledge Accumulation: a New Approach to Continual Learning
Learning from non-stationary data remains a great challenge for machine ...
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Slanted Stixels: A way to represent steep streets
This work presents and evaluates a novel compact scene representation ba...
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Adversarial Learning of General Transformations for Data Augmentation
Data augmentation (DA) is fundamental against overfitting in large convo...
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Fourier-CPPNs for Image Synthesis
Compositional Pattern Producing Networks (CPPNs) are differentiable netw...
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Class-Based Styling: Real-time Localized Style Transfer with Semantic Segmentation
We propose a Class-Based Styling method (CBS) that can map different sty...
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Where are the Masks: Instance Segmentation with Image-level Supervision
A major obstacle in instance segmentation is that existing methods often...
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Instance Segmentation with Point Supervision
Instance segmentation methods often require costly per-pixel labels. We ...
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Knowledge Hypergraphs: Extending Knowledge Graphs Beyond Binary Relations
Knowledge graphs store facts using relations between pairs of entities. ...
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Context-Aware Visual Compatibility Prediction
How do we determine whether two or more clothing items are compatible or...
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Where are the Blobs: Counting by Localization with Point Supervision
Object counting is an important task in computer vision due to its growi...
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Slanted Stixels: Representing San Francisco's Steepest Streets
In this work we present a novel compact scene representation based on St...
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From Virtual to Real World Visual Perception using Domain Adaptation -- The DPM as Example
Supervised learning tends to produce more accurate classifiers than unsu...
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A Benchmark for Endoluminal Scene Segmentation of Colonoscopy Images
Colorectal cancer (CRC) is the third cause of cancer death worldwide. Cu...
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The One Hundred Layers Tiramisu: Fully Convolutional DenseNets for Semantic Segmentation
State-of-the-art approaches for semantic image segmentation are built on...
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Node-Adapt, Path-Adapt and Tree-Adapt:Model-Transfer Domain Adaptation for Random Forest
Random Forest (RF) is a successful paradigm for learning classifiers due...
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GPU-based Pedestrian Detection for Autonomous Driving
We propose a real-time pedestrian detection system for the embedded Nvid...
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GPU-accelerated real-time stixel computation
The Stixel World is a medium-level, compact representation of road scene...
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Embedded real-time stereo estimation via Semi-Global Matching on the GPU
Dense, robust and real-time computation of depth information from stereo...
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Hierarchical Adaptive Structural SVM for Domain Adaptation
A key topic in classification is the accuracy loss produced when the dat...
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Spatiotemporal Stacked Sequential Learning for Pedestrian Detection
Pedestrian classifiers decide which image windows contain a pedestrian. ...
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