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04/16/2023
Federated Learning of Shareable Bases for Personalization-Friendly Image Classification
Personalized federated learning (PFL) aims to harness the collective wis...
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04/14/2023
Identity Encoder for Personalized Diffusion
Many applications can benefit from personalized image generation models,...
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04/05/2023
Domain Generalization with Adversarial Intensity Attack for Medical Image Segmentation
Most statistical learning algorithms rely on an over-simplified assumpti...
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04/05/2023
Taming Encoder for Zero Fine-tuning Image Customization with Text-to-Image Diffusion Models
This paper proposes a method for generating images of customized objects...
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12/22/2022
On Calibrating Semantic Segmentation Models: Analysis and An Algorithm
We study the problem of semantic segmentation calibration. For image cla...
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10/14/2022
LESS: Label-Efficient Semantic Segmentation for LiDAR Point Clouds
Semantic segmentation of LiDAR point clouds is an important task in auto...
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08/17/2022
Open Long-Tailed Recognition in a Dynamic World
Real world data often exhibits a long-tailed and open-ended (with unseen...
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04/11/2022
medXGAN: Visual Explanations for Medical Classifiers through a Generative Latent Space
Despite the surge of deep learning in the past decade, some users are sk...
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03/15/2022
Surrogate Gap Minimization Improves Sharpness-Aware Training
The recently proposed Sharpness-Aware Minimization (SAM) improves genera...
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09/18/2021
Anti-Neuron Watermarking: Protecting Personal Data Against Unauthorized Neural Model Training
In this paper, we raise up an emerging personal data protection problem ...
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06/18/2021
Bridging the Gap Between Object Detection and User Intent via Query-Modulation
When interacting with objects through cameras, or pictures, users often ...
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06/03/2021
When Vision Transformers Outperform ResNets without Pretraining or Strong Data Augmentations
Vision Transformers (ViTs) and MLPs signal further efforts on replacing ...
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06/01/2021
Adversarially Adaptive Normalization for Single Domain Generalization
Single domain generalization aims to learn a model that performs well on...
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04/22/2021
VATT: Transformers for Multimodal Self-Supervised Learning from Raw Video, Audio and Text
We present a framework for learning multimodal representations from unla...
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04/12/2021
Class-Balanced Distillation for Long-Tailed Visual Recognition
Real-world imagery is often characterized by a significant imbalance of ...
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03/23/2021
Robust and Accurate Object Detection via Adversarial Learning
Data augmentation has become a de facto component for training high-perf...
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03/21/2021
MoViNets: Mobile Video Networks for Efficient Video Recognition
We present Mobile Video Networks (MoViNets), a family of computation and...
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02/17/2021
A Simple and Effective Use of Object-Centric Images for Long-Tailed Object Detection
Object frequencies in daily scenes follow a long-tailed distribution. Ma...
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02/14/2021
Large-Scale Meta-Learning with Continual Trajectory Shifting
Meta-learning of shared initialization parameters has shown to be highly...
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12/13/2020
Contrastive Learning for Label-Efficient Semantic Segmentation
Collecting labeled data for the task of semantic segmentation is expensi...
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11/23/2020
Ranking Neural Checkpoints
This paper is concerned with ranking many pre-trained deep neural networ...
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07/17/2020
Improving Object Detection with Selective Self-supervised Self-training
We study how to leverage Web images to augment human-curated object dete...
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07/16/2020
Complete Label: A Domain Adaptation Approach to Semantic Segmentation of LiDAR Point Clouds
We study an unsupervised domain adaptation problem for the semantic labe...
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06/25/2020
Smooth Adversarial Training
It is commonly believed that networks cannot be both accurate and robust...
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05/01/2020
When Ensembling Smaller Models is More Efficient than Single Large Models
Ensembling is a simple and popular technique for boosting evaluation per...
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03/31/2020
Neural Networks Are More Productive Teachers Than Human Raters: Active Mixup for Data-Efficient Knowledge Distillation from a Blackbox Model
We study how to train a student deep neural network for visual recogniti...
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03/24/2020
Rethinking Class-Balanced Methods for Long-Tailed Visual Recognition from a Domain Adaptation Perspective
Object frequency in the real world often follows a power law, leading to...
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01/08/2020
MACER: Attack-free and Scalable Robust Training via Maximizing Certified Radius
Adversarial training is one of the most popular ways to learn robust mod...
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12/25/2019
Look, Listen, and Act: Towards Audio-Visual Embodied Navigation
A crucial aspect of mobile intelligent agents is their ability to integr...
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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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09/08/2019
Compound Domain Adaptation in an Open World
Existing works on domain adaptation often assume clear boundaries betwee...
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09/02/2019
Domain Randomization and Pyramid Consistency: Simulation-to-Real Generalization without Accessing Target Domain Data
We propose to harness the potential of simulation for the semantic segme...
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08/26/2019
Constructing Self-motivated Pyramid Curriculums for Cross-Domain Semantic Segmentation: A Non-Adversarial Approach
We propose a new approach, called self-motivated pyramid curriculum doma...
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08/18/2019
A Fast and Accurate One-Stage Approach to Visual Grounding
We propose a simple, fast, and accurate one-stage approach to visual gro...
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06/16/2019
Defending Against Adversarial Attacks Using Random Forests
As deep neural networks (DNNs) have become increasingly important and po...
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05/01/2019
NATTACK: Learning the Distributions of Adversarial Examples for an Improved Black-Box Attack on Deep Neural Networks
Powerful adversarial attack methods are vital for understanding how to c...
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04/10/2019
Large-Scale Long-Tailed Recognition in an Open World
Real world data often have a long-tailed and open-ended distribution. A ...
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04/05/2019
Synthesized Policies for Transfer and Adaptation across Tasks and Environments
The ability to transfer in reinforcement learning is key towards buildin...
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02/25/2019
Joint Modeling of Dense and Incomplete Trajectories for Citywide Traffic Volume Inference
Real-time traffic volume inference is key to an intelligent city. It is ...
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12/24/2018
A Curriculum Domain Adaptation Approach to the Semantic Segmentation of Urban Scenes
During the last half decade, convolutional neural networks (CNNs) have t...
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12/16/2018
Classifier and Exemplar Synthesis for Zero-Shot Learning
Zero-shot learning (ZSL) enables solving a task without the need to see ...
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08/09/2018
Controllable Image-to-Video Translation: A Case Study on Facial Expression Generation
The recent advances in deep learning have made it possible to generate p...
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07/28/2018
Improving Sequential Determinantal Point Processes for Supervised Video Summarization
It is now much easier than ever before to produce videos. While the ubiq...
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07/20/2018
Optimize Deep Convolutional Neural Network with Ternarized Weights and High Accuracy
Deep convolution neural network has achieved great success in many artif...
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07/18/2018
Defend Deep Neural Networks Against Adversarial Examples via Fixed andDynamic Quantized Activation Functions
Recent studies have shown that deep neural networks (DNNs) are vulnerabl...
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07/11/2018
How Local is the Local Diversity? Reinforcing Sequential Determinantal Point Processes with Dynamic Ground Sets for Supervised Video Summarization
The large volume of video content and high viewing frequency demand auto...
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04/02/2018
End-to-End Learning of Motion Representation for Video Understanding
Despite the recent success of end-to-end learned representations, hand-c...
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03/21/2018
End-to-End Video Captioning with Multitask Reinforcement Learning
Although end-to-end (E2E) learning has led to promising performance on a...
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03/05/2018
Improving the Improved Training of Wasserstein GANs: A Consistency Term and Its Dual Effect
Despite being impactful on a variety of problems and applications, the g...
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02/08/2018
