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Beyond Short Clips: End-to-End Video-Level Learning with Collaborative Memories
The standard way of training video models entails sampling at each itera...
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Knowledge Evolution in Neural Networks
Deep learning relies on the availability of a large corpus of data (labe...
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SVMax: A Feature Embedding Regularizer
A neural network regularizer (e.g., weight decay) boosts performance by ...
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Responsible Disclosure of Generative Models Using Scalable Fingerprinting
Over the past six years, deep generative models have achieved a qualitat...
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The Lottery Ticket Hypothesis for Object Recognition
Recognition tasks, such as object recognition and keypoint estimation, h...
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SLADE: A Self-Training Framework For Distance Metric Learning
Most existing distance metric learning approaches use fully labeled data...
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Analyzing and Mitigating Compression Defects in Deep Learning
With the proliferation of deep learning methods, many computer vision pr...
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Hierarchical Contrastive Motion Learning for Video Action Recognition
One central question for video action recognition is how to model motion...
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ASAP-NMS: Accelerating Non-Maximum Suppression Using Spatially Aware Priors
The widely adopted sequential variant of Non Maximum Suppression (or Gre...
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A Generic Visualization Approach for Convolutional Neural Networks
Retrieval networks are essential for searching and indexing. Compared to...
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Layout Generation and Completion with Self-attention
We address the problem of layout generation for diverse domains such as ...
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Quantization Guided JPEG Artifact Correction
The JPEG image compression algorithm is the most popular method of image...
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Inclusive GAN: Improving Data and Minority Coverage in Generative Models
Generative Adversarial Networks (GANs) have brought about rapid progress...
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Making an Invisibility Cloak: Real World Adversarial Attacks on Object Detectors
We present a systematic study of adversarial attacks on state-of-the-art...
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A weakly supervised adaptive triplet loss for deep metric learning
We address the problem of distance metric learning in visual similarity ...
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STEP: Spatio-Temporal Progressive Learning for Video Action Detection
In this paper, we propose Spatio-TEmporal Progressive (STEP) action dete...
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Unsupervised Data Uncertainty Learning in Visual Retrieval Systems
We introduce an unsupervised formulation to estimate heteroscedastic unc...
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In Defense of the Triplet Loss for Visual Recognition
We employ triplet loss as a space embedding regularizer to boost classif...
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Exploring Uncertainty in Conditional Multi-Modal Retrieval Systems
We cast visual retrieval as a regression problem by posing triplet loss ...
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Deep Residual Learning in the JPEG Transform Domain
We introduce a general method of performing Residual Network inference a...
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Stacked Spatio-Temporal Graph Convolutional Networks for Action Segmentation
We propose novel Stacked Spatio-Temporal Graph Convolutional Networks (S...
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Attributing Fake Images to GANs: Analyzing Fingerprints in Generated Images
Research in computer graphics has been in pursuit of realistic image gen...
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Learning GAN fingerprints towards Image Attribution
Recent advances in Generative Adversarial Networks (GANs) have shown inc...
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Two Stream Self-Supervised Learning for Action Recognition
We present a self-supervised approach using spatio-temporal signals betw...
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Learning to Color from Language
Automatic colorization is the process of adding color to greyscale image...
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Deep Motion Boundary Detection
Motion boundary detection is a crucial yet challenging problem. Prior me...
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Class Subset Selection for Transfer Learning using Submodularity
In recent years, it is common practice to extract fully-connected layer ...
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Face-MagNet: Magnifying Feature Maps to Detect Small Faces
In this paper, we introduce the Face Magnifier Network (Face-MageNet), a...
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Boundary-sensitive Network for Portrait Segmentation
Compared to the general semantic segmentation problem, portrait segmenta...
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SSH: Single Stage Headless Face Detector
We introduce the Single Stage Headless (SSH) face detector. Unlike two s...
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The Amazing Mysteries of the Gutter: Drawing Inferences Between Panels in Comic Book Narratives
Visual narrative is often a combination of explicit information and judi...
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Weakly Supervised Learning of Heterogeneous Concepts in Videos
Typical textual descriptions that accompany online videos are 'weak': i....
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Learning Discriminative Features via Label Consistent Neural Network
Deep Convolutional Neural Networks (CNN) enforces supervised information...
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Learning Structured Ordinal Measures for Video based Face Recognition
This paper presents a structured ordinal measure method for video-based ...
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