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04/14/2023
Fairness in Visual Clustering: A Novel Transformer Clustering Approach
Promoting fairness for deep clustering models in unsupervised clustering...
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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...
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12/15/2022
Enhanced Training of Query-Based Object Detection via Selective Query Recollection
This paper investigates a phenomenon where query-based object detectors ...
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11/20/2022
An Embarrassingly Simple Baseline for Imbalanced Semi-Supervised Learning
Semi-supervised learning (SSL) has shown great promise in leveraging unl...
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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 ...
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08/15/2022
Conv-Adapter: Exploring Parameter Efficient Transfer Learning for ConvNets
While parameter efficient tuning (PET) methods have shown great potentia...
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08/12/2022
USB: A Unified Semi-supervised Learning Benchmark
Semi-supervised learning (SSL) improves model generalization by leveragi...
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05/15/2022
FreeMatch: Self-adaptive Thresholding for Semi-supervised Learning
Pseudo labeling and consistency regularization approaches with confidenc...
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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...
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04/01/2022
Unitail: Detecting, Reading, and Matching in Retail Scene
To make full use of computer vision technology in stores, it is required...
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08/25/2021
Deep Reinforcement Learning in Computer Vision: A Comprehensive Survey
Deep reinforcement learning augments the reinforcement learning framewor...
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04/01/2021
Is Label Smoothing Truly Incompatible with Knowledge Distillation: An Empirical Study
This work aims to empirically clarify a recently discovered perspective ...
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03/30/2021
Unsupervised Disentanglement of Linear-Encoded Facial Semantics
We propose a method to disentangle linear-encoded facial semantics from ...
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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 ...
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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...
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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...
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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...
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11/15/2020
Online Ensemble Model Compression using Knowledge Distillation
This paper presents a novel knowledge distillation based model compressi...
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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...
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05/13/2020
Binarizing MobileNet via Evolution-based Searching
Binary Neural Networks (BNNs), known to be one among the effectively com...
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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...
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03/11/2020
Rethinking Image Mixture for Unsupervised Visual Representation Learning
In supervised learning, smoothing label/prediction distribution in neura...
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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...
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02/12/2020
Solving Missing-Annotation Object Detection with Background Recalibration Loss
This paper focuses on a novel and challenging detection scenario: A majo...
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11/27/2019
Soft Anchor-Point Object Detection
Recently, anchor-free detectors have shown great potential to outperform...
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11/24/2019
Towards a Hypothesis on Visual Transformation based Self-Supervision
We propose the first qualitative hypothesis characterizing the behavior ...
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11/13/2019
Learning Non-Parametric Invariances from Data with Permanent Random Connectomes
One of the fundamental problems in supervised classification and in mach...
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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...
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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...
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07/29/2019
MoBiNet: A Mobile Binary Network for Image Classification
MobileNet and Binary Neural Networks are two among the most widely used ...
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03/17/2019
Proximal Splitting Networks for Image Restoration
Image restoration problems are typically ill-posed requiring the design ...
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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...
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12/19/2018
RankGAN: A Maximum Margin Ranking GAN for Generating Faces
We present a new stage-wise learning paradigm for training generative ad...
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10/10/2018
Deep Recurrent Level Set for Segmenting Brain Tumors
Variational Level Set (VLS) has been a widely used method in medical seg...
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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...
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06/05/2018
Perturbative Neural Networks
Convolutional neural networks are witnessing wide adoption in computer v...
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02/28/2018
Ring loss: Convex Feature Normalization for Face Recognition
We motivate and present Ring loss, a simple and elegant feature normaliz...
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02/25/2018
Seeing Small Faces from Robust Anchor's Perspective
This paper introduces a novel anchor design to support anchor-based face...
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01/14/2018
Non-Parametric Transformation Networks
ConvNets have been very effective in many applications where it is requi...
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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...
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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...
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10/24/2017
Max-Margin Invariant Features from Transformed Unlabeled Data
The study of representations invariant to common transformations of the ...
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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...
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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...
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02/24/2017
How ConvNets model Non-linear Transformations
In this paper, we theoretically address three fundamental problems invol...
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01/30/2017
Emergence of Selective Invariance in Hierarchical Feed Forward Networks
Many theories have emerged which investigate how in- variance is generat...
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12/16/2016
Towards a Deep Learning Framework for Unconstrained Face Detection
Robust face detection is one of the most important pre-processing steps ...
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08/22/2016
Local Binary Convolutional Neural Networks
We propose local binary convolution (LBC), an efficient alternative to c...
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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...
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11/18/2015
