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05/05/2023
Human Attention-Guided Explainable Artificial Intelligence for Computer Vision Models
We examined whether embedding human attention knowledge into saliency-ba...
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04/13/2023
ODAM: Gradient-based instance-specific visual explanations for object detection
We propose the gradient-weighted Object Detector Activation Maps (ODAM),...
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04/02/2023
DropMAE: Masked Autoencoders with Spatial-Attention Dropout for Tracking Tasks
In this paper, we study masked autoencoder (MAE) pretraining on videos f...
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03/20/2023
TWINS: A Fine-Tuning Framework for Improved Transferability of Adversarial Robustness and Generalization
Recent years have seen the ever-increasing importance of pre-trained mod...
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10/11/2022
Boosting Adversarial Robustness From The Perspective of Effective Margin Regularization
The adversarial vulnerability of deep neural networks (DNNs) has been ac...
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07/04/2022
Pareto Optimization for Active Learning under Out-of-Distribution Data Scenarios
Pool-based Active Learning (AL) has achieved great success in minimizing...
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05/03/2022
Cross-View Cross-Scene Multi-View Crowd Counting
Multi-view crowd counting has been previously proposed to utilize multi-...
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04/08/2022
On Distinctive Image Captioning via Comparing and Reweighting
Recent image captioning models are achieving impressive results based on...
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03/25/2022
A Comparative Survey of Deep Active Learning
Active Learning (AL) is a set of techniques for reducing labeling cost b...
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03/08/2022
A Lightweight and Detector-free 3D Single Object Tracker on Point Clouds
Recent works on 3D single object tracking treat the tracking as a target...
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10/10/2021
BEV-Net: Assessing Social Distancing Compliance by Joint People Localization and Geometric Reasoning
Social distancing, an essential public health measure to limit the sprea...
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08/20/2021
Group-based Distinctive Image Captioning with Memory Attention
Describing images using natural language is widely known as image captio...
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07/04/2021
Multiple-criteria Based Active Learning with Fixed-size Determinantal Point Processes
Active learning aims to achieve greater accuracy with less training data...
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02/06/2021
The Implicit Biases of Stochastic Gradient Descent on Deep Neural Networks with Batch Normalization
Deep neural networks with batch normalization (BN-DNNs) are invariant to...
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01/27/2021
Bayesian Nested Neural Networks for Uncertainty Calibration and Adaptive Compression
Nested networks or slimmable networks are neural networks whose architec...
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12/02/2020
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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08/07/2020
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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07/18/2020
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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07/14/2020
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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07/13/2020
Fine-Grained Crowd Counting
Current crowd counting algorithms are only concerned about the number of...
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07/08/2020
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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06/09/2020
Over-crowdedness Alert! Forecasting the Future Crowd Distribution
In recent years, vision-based crowd analysis has been studied extensivel...
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03/18/2020
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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08/14/2019
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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07/28/2019
ROAM: Recurrently Optimizing Tracking Model
Online updating a tracking model to adapt to object appearance variation...
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07/12/2019
Visual Tracking via Dynamic Memory Networks
Template-matching methods for visual tracking have gained popularity rec...
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05/29/2019
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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03/28/2019
Describing like humans: on diversity in image captioning
Recently, the state-of-the-art models for image captioning have overtake...
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01/13/2019
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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10/30/2018
Gated Hierarchical Attention for Image Captioning
Attention modules connecting encoder and decoders have been widely appli...
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10/17/2018
EMHMM Simulation Study
Eye Movement analysis with Hidden Markov Models (EMHMM) is a method for ...
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05/23/2018
CNN+CNN: Convolutional Decoders for Image Captioning
Image captioning is a challenging task that combines the field of comput...
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03/20/2018
Learning Dynamic Memory Networks for Object Tracking
Template-matching methods for visual tracking have gained popularity rec...
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08/13/2017
Recurrent Filter Learning for Visual Tracking
Recently using convolutional neural networks (CNNs) has gained popularit...
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05/29/2017
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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03/17/2017
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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11/21/2016
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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06/13/2014
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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02/10/2014
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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11/25/2013
On Approximate Inference for Generalized Gaussian Process Models
A generalized Gaussian process model (GGPM) is a unifying framework that...
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10/24/2012
Clustering hidden Markov models with variational HEM
The hidden Markov model (HMM) is a widely-used generative model that cop...
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09/06/2011
