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Wide-Area Crowd Counting: Multi-View Fusion Networks for Counting in Large Scenes
Crowd counting in single-view images has achieved outstanding performanc...
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Improve Generalization and Robustness of Neural Networks via Weight Scale Shifting Invariant Regularizations
Using weight decay to penalize the L2 norms of weights in neural network...
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Tracking-by-Counting: Using Network Flows on Crowd Density Maps for Tracking Multiple Targets
State-of-the-art multi-object tracking (MOT) methods follow the tracking...
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Compare and Reweight: Distinctive Image Captioning Using Similar Images Sets
A wide range of image captioning models has been developed, achieving si...
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Fine-Grained Crowd Counting
Current crowd counting algorithms are only concerned about the number of...
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Single-Frame based Deep View Synchronization for Unsynchronized Multi-Camera Surveillance
Multi-camera surveillance has been an active research topic for understa...
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Over-crowdedness Alert! Forecasting the Future Crowd Distribution
In recent years, vision-based crowd analysis has been studied extensivel...
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3D Crowd Counting via Multi-View Fusion with 3D Gaussian Kernels
Crowd counting has been studied for decades and a lot of works have achi...
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Towards Diverse and Accurate Image Captions via Reinforcing Determinantal Point Process
Although significant progress has been made in the field of automatic im...
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ROAM: Recurrently Optimizing Tracking Model
Online updating a tracking model to adapt to object appearance variation...
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Visual Tracking via Dynamic Memory Networks
Template-matching methods for visual tracking have gained popularity rec...
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Accelerating Monte Carlo Bayesian Inference via Approximating Predictive Uncertainty over Simplex
Estimating the uncertainty of a Bayesian model has been investigated for...
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Describing like humans: on diversity in image captioning
Recently, the state-of-the-art models for image captioning have overtake...
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A Fully Bayesian Infinite Generative Model for Dynamic Texture Segmentation
Generative dynamic texture models (GDTMs) are widely used for dynamic te...
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Gated Hierarchical Attention for Image Captioning
Attention modules connecting encoder and decoders have been widely appli...
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EMHMM Simulation Study
Eye Movement analysis with Hidden Markov Models (EMHMM) is a method for ...
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CNN+CNN: Convolutional Decoders for Image Captioning
Image captioning is a challenging task that combines the field of comput...
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Learning Dynamic Memory Networks for Object Tracking
Template-matching methods for visual tracking have gained popularity rec...
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Recurrent Filter Learning for Visual Tracking
Recently using convolutional neural networks (CNNs) has gained popularit...
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Beyond Counting: Comparisons of Density Maps for Crowd Analysis Tasks - Counting, Detection, and Tracking
For crowded scenes, the accuracy of object-based computer vision methods...
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Color Orchestra: Ordering Color Palettes for Interpolation and Prediction
Color theme or color palette can deeply influence the quality and the fe...
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Crowd Counting by Adapting Convolutional Neural Networks with Side Information
Computer vision tasks often have side information available that is help...
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Heterogeneous Multi-task Learning for Human Pose Estimation with Deep Convolutional Neural Network
We propose an heterogeneous multi-task learning framework for human pose...
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Leveraging Long-Term Predictions and Online-Learning in Agent-based Multiple Person Tracking
We present a multiple-person tracking algorithm, based on combining part...
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On Approximate Inference for Generalized Gaussian Process Models
A generalized Gaussian process model (GGPM) is a unifying framework that...
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Clustering hidden Markov models with variational HEM
The hidden Markov model (HMM) is a widely-used generative model that cop...
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Tech Report A Variational HEM Algorithm for Clustering Hidden Markov Models
The hidden Markov model (HMM) is a generative model that treats sequenti...
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