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04/18/2022
Neural Space-filling Curves
We present Neural Space-filling Curves (SFCs), a data-driven approach to...
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01/31/2022
Leveraging Bitstream Metadata for Fast and Accurate Video Compression Correction
Video compression is a central feature of the modern internet powering t...
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10/11/2021
Learning Realistic Human Reposing using Cyclic Self-Supervision with 3D Shape, Pose, and Appearance Consistency
Synthesizing images of a person in novel poses from a single image is a ...
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05/20/2021
More Than Just Attention: Learning Cross-Modal Attentions with Contrastive Constraints
Attention mechanisms have been widely applied to cross-modal tasks such ...
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05/16/2021
Unsupervised Super-Resolution of Satellite Imagery for High Fidelity Material Label Transfer
Urban material recognition in remote sensing imagery is a highly relevan...
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05/06/2021
VideoLT: Large-scale Long-tailed Video Recognition
Label distributions in real-world are oftentimes long-tailed and imbalan...
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04/24/2021
M3DeTR: Multi-representation, Multi-scale, Mutual-relation 3D Object Detection with Transformers
We present a novel architecture for 3D object detection, M3DeTR, which c...
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04/02/2021
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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03/09/2021
Knowledge Evolution in Neural Networks
Deep learning relies on the availability of a large corpus of data (labe...
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03/04/2021
SVMax: A Feature Embedding Regularizer
A neural network regularizer (e.g., weight decay) boosts performance by ...
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12/16/2020
Responsible Disclosure of Generative Models Using Scalable Fingerprinting
Over the past six years, deep generative models have achieved a qualitat...
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12/08/2020
The Lottery Ticket Hypothesis for Object Recognition
Recognition tasks, such as object recognition and keypoint estimation, h...
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11/20/2020
SLADE: A Self-Training Framework For Distance Metric Learning
Most existing distance metric learning approaches use fully labeled data...
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11/17/2020
Analyzing and Mitigating Compression Defects in Deep Learning
With the proliferation of deep learning methods, many computer vision pr...
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07/20/2020
Hierarchical Contrastive Motion Learning for Video Action Recognition
One central question for video action recognition is how to model motion...
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07/19/2020
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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07/19/2020
A Generic Visualization Approach for Convolutional Neural Networks
Retrieval networks are essential for searching and indexing. Compared to...
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06/25/2020
Layout Generation and Completion with Self-attention
We address the problem of layout generation for diverse domains such as ...
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04/17/2020
Quantization Guided JPEG Artifact Correction
The JPEG image compression algorithm is the most popular method of image...
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04/07/2020
Inclusive GAN: Improving Data and Minority Coverage in Generative Models
Generative Adversarial Networks (GANs) have brought about rapid progress...
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10/31/2019
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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09/27/2019
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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04/19/2019
STEP: Spatio-Temporal Progressive Learning for Video Action Detection
In this paper, we propose Spatio-TEmporal Progressive (STEP) action dete...
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02/07/2019
Unsupervised Data Uncertainty Learning in Visual Retrieval Systems
We introduce an unsupervised formulation to estimate heteroscedastic unc...
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01/24/2019
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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01/23/2019
Exploring Uncertainty in Conditional Multi-Modal Retrieval Systems
We cast visual retrieval as a regression problem by posing triplet loss ...
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12/31/2018
Deep Residual Learning in the JPEG Transform Domain
We introduce a general method of performing Residual Network inference a...
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11/26/2018
Stacked Spatio-Temporal Graph Convolutional Networks for Action Segmentation
We propose novel Stacked Spatio-Temporal Graph Convolutional Networks (S...
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11/20/2018
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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11/20/2018
Learning GAN fingerprints towards Image Attribution
Recent advances in Generative Adversarial Networks (GANs) have shown inc...
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06/16/2018
Two Stream Self-Supervised Learning for Action Recognition
We present a self-supervised approach using spatio-temporal signals betw...
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04/17/2018
Learning to Color from Language
Automatic colorization is the process of adding color to greyscale image...
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04/13/2018
Deep Motion Boundary Detection
Motion boundary detection is a crucial yet challenging problem. Prior me...
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03/30/2018
Class Subset Selection for Transfer Learning using Submodularity
In recent years, it is common practice to extract fully-connected layer ...
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03/14/2018
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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12/22/2017
Boundary-sensitive Network for Portrait Segmentation
Compared to the general semantic segmentation problem, portrait segmenta...
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08/14/2017
SSH: Single Stage Headless Face Detector
We introduce the Single Stage Headless (SSH) face detector. Unlike two s...
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11/16/2016
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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07/12/2016
Weakly Supervised Learning of Heterogeneous Concepts in Videos
Typical textual descriptions that accompany online videos are 'weak': i....
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02/03/2016
Learning Discriminative Features via Label Consistent Neural Network
Deep Convolutional Neural Networks (CNN) enforces supervised information...
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07/09/2015