Marios Savvides

research

∙ 04/14/2023

Fairness in Visual Clustering: A Novel Transformer Clustering Approach

Promoting fairness for deep clustering models in unsupervised clustering...

0 Xuan-Bac Nguyen, et al. ∙

research

∙ 01/26/2023

SoftMatch: Addressing the Quantity-Quality Trade-off in Semi-supervised Learning

The critical challenge of Semi-Supervised Learning (SSL) is how to effec...

0 Hao Chen, et al. ∙

research

∙ 12/15/2022

Enhanced Training of Query-Based Object Detection via Selective Query Recollection

This paper investigates a phenomenon where query-based object detectors ...

0 Fangyi Chen, et al. ∙

research

∙ 11/20/2022

An Embarrassingly Simple Baseline for Imbalanced Semi-Supervised Learning

Semi-supervised learning (SSL) has shown great promise in leveraging unl...

0 Hao Chen, et al. ∙

research

∙ 09/11/2022

Vec2Face-v2: Unveil Human Faces from their Blackbox Features via Attention-based Network in Face Recognition

In this work, we investigate the problem of face reconstruction given a ...

0 Thanh-Dat Truong, et al. ∙

research

∙ 08/15/2022

Conv-Adapter: Exploring Parameter Efficient Transfer Learning for ConvNets

While parameter efficient tuning (PET) methods have shown great potentia...

0 Hao Chen, et al. ∙

research

∙ 08/12/2022

USB: A Unified Semi-supervised Learning Benchmark

Semi-supervised learning (SSL) improves model generalization by leveragi...

0 Yidong Wang, et al. ∙

research

∙ 05/15/2022

FreeMatch: Self-adaptive Thresholding for Semi-supervised Learning

Pseudo labeling and consistency regularization approaches with confidenc...

0 Yidong Wang, et al. ∙

research

∙ 04/07/2022

Powering Finetuning in Few-shot Learning: Domain-Agnostic Feature Adaptation with Rectified Class Prototypes

In recent works, utilizing a deep network trained on meta-training set s...

0 Ran Tao, et al. ∙

research

∙ 04/01/2022

Unitail: Detecting, Reading, and Matching in Retail Scene

To make full use of computer vision technology in stores, it is required...

0 Fangyi Chen, et al. ∙

research

∙ 08/25/2021

Deep Reinforcement Learning in Computer Vision: A Comprehensive Survey

Deep reinforcement learning augments the reinforcement learning framewor...

0 Ngan Le, et al. ∙

research

∙ 04/01/2021

Is Label Smoothing Truly Incompatible with Knowledge Distillation: An Empirical Study

This work aims to empirically clarify a recently discovered perspective ...

0 Zhiqiang Shen, et al. ∙

research

∙ 03/30/2021

Unsupervised Disentanglement of Linear-Encoded Facial Semantics

We propose a method to disentangle linear-encoded facial semantics from ...

0 Yutong Zheng, et al. ∙

research

∙ 03/02/2021

Semantic Relation Reasoning for Shot-Stable Few-Shot Object Detection

Few-shot object detection is an imperative and long-lasting problem due ...

0 Chenchen Zhu, et al. ∙

research

∙ 02/17/2021

S2-BNN: Bridging the Gap Between Self-Supervised Real and 1-bit Neural Networks via Guided Distribution Calibration

Previous studies dominantly target at self-supervised learning on real-v...

0 Zhiqiang Shen, et al. ∙

research

∙ 02/08/2021

Partial Is Better Than All: Revisiting Fine-tuning Strategy for Few-shot Learning

The goal of few-shot learning is to learn a classifier that can recogniz...

0 Zhiqiang Shen, et al. ∙

research

∙ 12/03/2020

A Multi-task Contextual Atrous Residual Network for Brain Tumor Detection Segmentation

In recent years, deep neural networks have achieved state-of-the-art per...

0 Ngan Le, et al. ∙

research

∙ 11/15/2020

Online Ensemble Model Compression using Knowledge Distillation

This paper presents a novel knowledge distillation based model compressi...

0 Devesh Walawalkar, et al. ∙

research

∙ 09/17/2020

MEAL V2: Boosting Vanilla ResNet-50 to 80 without Tricks

In this paper, we introduce a simple yet effective approach that can boo...

0 Zhiqiang Shen, et al. ∙

research

∙ 05/13/2020

Binarizing MobileNet via Evolution-based Searching

Binary Neural Networks (BNNs), known to be one among the effectively com...

0 Hai Phan, et al. ∙

research

∙ 03/29/2020

Attentive CutMix: An Enhanced Data Augmentation Approach for Deep Learning Based Image Classification

Convolutional neural networks (CNN) are capable of learning robust repre...

0 Devesh Walawalkar, et al. ∙

research

∙ 03/11/2020

Rethinking Image Mixture for Unsupervised Visual Representation Learning

In supervised learning, smoothing label/prediction distribution in neura...

8 Zhiqiang Shen, et al. ∙

research

∙ 03/07/2020

ReActNet: Towards Precise Binary Neural Network with Generalized Activation Functions

In this paper, we propose several ideas for enhancing a binary network t...

0 Zechun Liu, et al. ∙

research

∙ 02/12/2020

Solving Missing-Annotation Object Detection with Background Recalibration Loss

This paper focuses on a novel and challenging detection scenario: A majo...

0 Han Zhang, et al. ∙

research

∙ 11/27/2019

Soft Anchor-Point Object Detection

Recently, anchor-free detectors have shown great potential to outperform...

0 Chenchen Zhu, et al. ∙

research

∙ 11/24/2019

Towards a Hypothesis on Visual Transformation based Self-Supervision

We propose the first qualitative hypothesis characterizing the behavior ...

0 Dipan K. Pal, et al. ∙

research

∙ 11/13/2019

Learning Non-Parametric Invariances from Data with Permanent Random Connectomes

One of the fundamental problems in supervised classification and in mach...

0 Dipan K. Pal, et al. ∙

research

∙ 11/06/2019

SCL: Towards Accurate Domain Adaptive Object Detection via Gradient Detach Based Stacked Complementary Losses

Unsupervised domain adaptive object detection aims to learn a robust det...

24 Zhiqiang Shen, et al. ∙

research

∙ 08/22/2019

Adversarial-Based Knowledge Distillation for Multi-Model Ensemble and Noisy Data Refinement

Generic Image recognition is a fundamental and fairly important visual p...

24 Zhiqiang Shen, et al. ∙

research

∙ 07/29/2019

MoBiNet: A Mobile Binary Network for Image Classification

MobileNet and Binary Neural Networks are two among the most widely used ...

2 Hai Phan, et al. ∙

research

∙ 03/17/2019

Proximal Splitting Networks for Image Restoration

Image restoration problems are typically ill-posed requiring the design ...

0 Raied Aljadaany, et al. ∙

research

∙ 03/02/2019

Feature Selective Anchor-Free Module for Single-Shot Object Detection

We motivate and present feature selective anchor-free (FSAF) module, a s...

0 Chenchen Zhu, et al. ∙

research

∙ 12/19/2018

RankGAN: A Maximum Margin Ranking GAN for Generating Faces

We present a new stage-wise learning paradigm for training generative ad...

12 Rahul Dey, et al. ∙

research

∙ 10/10/2018

Deep Recurrent Level Set for Segmenting Brain Tumors

Variational Level Set (VLS) has been a widely used method in medical seg...

0 T. Hoang Ngan Le, et al. ∙

research

∙ 09/23/2018

Softer-NMS: Rethinking Bounding Box Regression for Accurate Object Detection

Non-maximum suppression (NMS) is essential for state-of-the-art object d...

0 Yihui He, et al. ∙

research

∙ 06/05/2018

Perturbative Neural Networks

Convolutional neural networks are witnessing wide adoption in computer v...

2 Felix Juefei-Xu, et al. ∙

research

∙ 02/28/2018

Ring loss: Convex Feature Normalization for Face Recognition

We motivate and present Ring loss, a simple and elegant feature normaliz...

1 Yutong Zheng, et al. ∙

research

∙ 02/25/2018

Seeing Small Faces from Robust Anchor's Perspective

This paper introduces a novel anchor design to support anchor-based face...

0 Chenchen Zhu, et al. ∙

research

∙ 01/14/2018

Non-Parametric Transformation Networks

ConvNets have been very effective in many applications where it is requi...

0 Dipan K. Pal, et al. ∙

research

∙ 11/28/2017

Learning from Longitudinal Face Demonstration - Where Tractable Deep Modeling Meets Inverse Reinforcement Learning

This paper presents a novel Generative Probabilistic Modeling under an I...

0 Chi Nhan Duong, et al. ∙

research

∙ 10/26/2017

Class Correlation affects Single Object Localization using Pre-trained ConvNets

The problem of object localization has become one of the mainstream prob...

0 Pokkalla Harsha Vardhan, et al. ∙

research

∙ 10/24/2017

Max-Margin Invariant Features from Transformed Unlabeled Data

The study of representations invariant to common transformations of the ...

0 Dipan K. Pal, et al. ∙

research

∙ 07/18/2017

Faster Than Real-time Facial Alignment: A 3D Spatial Transformer Network Approach in Unconstrained Poses

Facial alignment involves finding a set of landmark points on an image w...

0 Chandrasekhar Bhagavatula, et al. ∙

research

∙ 03/24/2017

Temporal Non-Volume Preserving Approach to Facial Age-Progression and Age-Invariant Face Recognition

Modeling the long-term facial aging process is extremely challenging due...

0 Chi Nhan Duong, et al. ∙

research

∙ 02/24/2017

How ConvNets model Non-linear Transformations

In this paper, we theoretically address three fundamental problems invol...

0 Dipan K. Pal, et al. ∙

research

∙ 01/30/2017

Emergence of Selective Invariance in Hierarchical Feed Forward Networks

Many theories have emerged which investigate how in- variance is generat...

0 Dipan K. Pal, et al. ∙

research

∙ 12/16/2016

Towards a Deep Learning Framework for Unconstrained Face Detection

Robust face detection is one of the most important pre-processing steps ...

0 Yutong Zheng, et al. ∙

research

∙ 08/22/2016

Local Binary Convolutional Neural Networks

We propose local binary convolution (LBC), an efficient alternative to c...

0 Felix Juefei-Xu, et al. ∙

research

∙ 06/17/2016

CMS-RCNN: Contextual Multi-Scale Region-based CNN for Unconstrained Face Detection

Robust face detection in the wild is one of the ultimate components to s...

0 Chenchen Zhu, et al. ∙

research

∙ 11/18/2015

Unitary-Group Invariant Kernels and Features from Transformed Unlabeled Data

The study of representations invariant to common transformations of the ...

0 Dipan K. Pal, et al. ∙

Marios Savvides

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