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06/07/2023
RefineVIS: Video Instance Segmentation with Temporal Attention Refinement
We introduce a novel framework called RefineVIS for Video Instance Segme...
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04/12/2023
Adaptive Human Matting for Dynamic Videos
The most recent efforts in video matting have focused on eliminating tri...
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04/10/2023
Binary Latent Diffusion
In this paper, we show that a binary latent space can be explored for co...
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02/02/2023
Energy-Inspired Self-Supervised Pretraining for Vision Models
Motivated by the fact that forward and backward passes of a deep network...
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10/11/2022
Observability Analysis of Graph SLAM-Based Joint Calibration of Multiple Microphone Arrays and Sound Source Localization
Multiple microphone arrays have many applications in robot audition, inc...
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06/14/2022
Consistent Video Instance Segmentation with Inter-Frame Recurrent Attention
Video instance segmentation aims at predicting object segmentation masks...
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03/26/2022
Augmenting Knowledge Graphs for Better Link Prediction
Embedding methods have demonstrated robust performance on the task of li...
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03/23/2022
Deep Frequency Filtering for Domain Generalization
Improving the generalization capability of Deep Neural Networks (DNNs) i...
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12/13/2021
Lifelong Unsupervised Domain Adaptive Person Re-identification with Coordinated Anti-forgetting and Adaptation
Unsupervised domain adaptive person re-identification (ReID) has been ex...
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11/30/2021
MMPTRACK: Large-scale Densely Annotated Multi-camera Multiple People Tracking Benchmark
Multi-camera tracking systems are gaining popularity in applications tha...
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04/01/2021
TransMOT: Spatial-Temporal Graph Transformer for Multiple Object Tracking
Tracking multiple objects in videos relies on modeling the spatial-tempo...
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03/09/2021
Computational Impact Time Guidance: A Learning-Based Prediction-Correction Approach
This paper investigates the problem of impact-time-control and proposes ...
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08/13/2020
Graph-Based Fuzz Testing for Deep Learning Inference Engine
Testing deep learning (DL) systems are increasingly crucial as the incre...
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07/22/2020
Coarse Graining Molecular Dynamics with Graph Neural Networks
Coarse graining enables the investigation of molecular dynamics for larg...
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05/04/2020
Ensemble Learning of Coarse-Grained Molecular Dynamics Force Fields with a Kernel Approach
Gradient-domain machine learning (GDML) is an accurate and efficient app...
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12/30/2019
RC-DARTS: Resource Constrained Differentiable Architecture Search
Recent advances show that Neural Architectural Search (NAS) method is ab...
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11/21/2019
Adversarial Examples Improve Image Recognition
Adversarial examples are commonly viewed as a threat to ConvNets. Here w...
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12/04/2018
Machine Learning of coarse-grained Molecular Dynamics Force Fields
Atomistic or ab-initio molecular dynamics simulations are widely used to...
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12/01/2018
NOTE-RCNN: NOise Tolerant Ensemble RCNN for Semi-Supervised Object Detection
The labeling cost of large number of bounding boxes is one of the main c...
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02/06/2018
Training Generative Adversarial Networks via Primal-Dual Subgradient Methods: A Lagrangian Perspective on GAN
We relate the minimax game of generative adversarial networks (GANs) to ...
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05/20/2016
Localizing by Describing: Attribute-Guided Attention Localization for Fine-Grained Recognition
A key challenge in fine-grained recognition is how to find and represent...
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04/15/2016
CNN-RNN: A Unified Framework for Multi-label Image Classification
While deep convolutional neural networks (CNNs) have shown a great succe...
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03/22/2016
Fully Convolutional Attention Networks for Fine-Grained Recognition
Fine-grained recognition is challenging due to its subtle local inter-cl...
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11/10/2015
Attention to Scale: Scale-aware Semantic Image Segmentation
Incorporating multi-scale features in fully convolutional neural network...
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04/25/2015
Learning like a Child: Fast Novel Visual Concept Learning from Sentence Descriptions of Images
In this paper, we address the task of learning novel visual concepts, an...
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12/20/2014
Deep Captioning with Multimodal Recurrent Neural Networks (m-RNN)
In this paper, we present a multimodal Recurrent Neural Network (m-RNN) ...
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10/04/2014
Explain Images with Multimodal Recurrent Neural Networks
In this paper, we present a multimodal Recurrent Neural Network (m-RNN) ...
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05/12/2014
Cross-view Action Modeling, Learning and Recognition
Existing methods on video-based action recognition are generally view-de...
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04/17/2014