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CV--PaperDaily

Updated at irregular intervals. Notes are attached to PDF files.

Archive

2022

  • [TMM] Latent Feature Pyramid Network for Object Detection

2021

  • [AAAI] Learning Modulated Loss for Rotated Object Detection
  • [AAAI] R3Det: Refined Single-Stage Detector with Feature Refinement for Rotating Object
  • [ICCV] Reconcile Prediction Consistency for Balanced Object Detection
  • [CVPR] You Only Look One-level Feature
  • [CVPR] Boundary IoU: Improving Object-Centric Image Segmentation Evaluation
  • [CVPR] Coordinate Attention for Efficient Mobile Network Design
  • [CVPR] Dot Distance for Tiny Object Detection in Aerial Images
  • [CVPR] IQDet: Instance-wise Quality Distribution Sampling for Object Detection
  • [ICML] Rethinking Rotated Object Detection with Gaussian Wasserstein Distance Loss
  • [ICLR] Deformable DETR: Deformable Transformers for End-to-End Object Detection
  • [WACV] Disentangled Contour Learning for Quadrilateral Text Detection
  • [BMVC] Mask-aware IoU for Anchor Assignment in Real-time Instance Segmentation
  • [NeurIPS] Alpha-IoU: A Family of Power Intersection over Union Losses for Bounding Box Regression
  • [NeurIPS] Dynamic Resolution Network
  • [IROS] Object-to-Scene: Learning to Transfer Object Knowledge to Indoor Scene Recognition
  • [ACM MM] Decoupled IoU Regression for Object Detection
  • [JSTARS] Arbitrary-Oriented Ship Detection through Center-Head Point Extraction
  • [TIP] GSDet: Object Detection in Aerial Images Based on Scale Reasoning
  • [TIP] HCE: Hierarchical Context Embedding for Region-Based Object Detection
  • [TGRS] SKNet: Detecting Rotated Ships as Keypoints in Optical Remote Sensing Images
  • [TGRS] Laplacian Feature Pyramid Network for Object Detection in VHR Optical Remote Sensing Images
  • [NCAA] Hilbert sEMG data scanning for hand gesture recognition based on deep learning
  • [IVC] Weighted boxes fusion: Ensembling boxes from different object detection models
  • [Knowledge-Based Systems] PRPN: Progressive region prediction network for natural scene text detection
  • Confidence Propagation Cluster: Unleash Full Potential of Object Detectors
  • FAIR1M: A Benchmark Dataset for Fine-grained Object Recognition in High-Resolution Remote Sensing Imagery
  • Object Detection in Aerial Images A Large-Scale Benchmark and Challenges
  • Gaussian Guided IoU: A Better Metric for Balanced Learning on Object Detection
  • MOD: Benchmark for Military Object Detection
  • Location-Sensitive Visual Recognition with Cross-IOU Loss
  • Anchor Pruning for Object Detection
  • SCALoss: Side and Corner Aligned Loss for Bounding Box Regression

2020

  • [AAAI] Arbitrary-Oriented Object Detection with Circular Smooth Label
  • [AAAI] CBNet: A Novel Composite Backbone Network Architecture for Object Detection
  • [AAAI] Distance-IoU
  • [AAAI] Progressive Feature Polishing Network for Salient Object Detection
  • [BMVC] Cascade RetinaNet: Maintaining Consistency for Single-Stage Object Detection
  • [CVPR] AugFPN: Improving Multi-scale Feature Learning for Object Detection
  • [CVPR] ContourNet: Taking a Further Step toward Accurate Arbitrary-shaped Scene Text Detection
  • [CVPR] Delving into Online High-quality Anchors Mining for Detecting Outer Faces
  • [CVPR] Detection in Crowded Scenes One Proposal, Multiple Predictions
  • [CVPR] Learning from Noisy Anchors for One-stage Object Detection
  • [CVPR] Multiple Anchor Learning for Visual Object Detection
  • [CVPR] PolarMask: Single Shot Instance Segmentation with Polar Representation
  • [CVPR] Revisiting the Sibling Head in Object Detector
  • [ECCV] Dynamic R-CNN : Towards High Quality Object Detection via Dynamic Training
  • [ECCV] PIoU Loss: Towards Accurate Oriented Object Detection in Complex Environments
  • [ECCV] Probabilistic Anchor Assignment with IoU Prediction for Object Detection
  • [ECCV] Rotation-robust Intersection over Union for 3D Object Detection
  • [ECCV] End-to-End Object Detection with Transformers
  • [ECCV] Side-Aware Boundary Localization for More Precise Object Detection
  • [JSTARS] Learning Point-guided Localization for Detection in Remote Sensing Images
  • [TGRS] Adaptive Period Embedding for Representing Oriented Objects in Aerial Images
  • [TCSVT] Joint Anchor-Feature Refinement for Real-Time Accurate Object Detection in Images and Videos
  • [Neurocomputing] Recent Advances in Deep Learning for Object Detection
  • [Neurocomputing] Single-Shot Bidirectional Pyramid Networks for High-Quality Object Detection
  • [Remote Sens.] EFN: Field-based Object Detection for Aerial Images
  • [Remote Sens.] Single-Stage Rotation-Decoupled Detector for Oriented Object
  • [Remote Sens.] A2S-Det: Efficiency Anchor Matching in Aerial Image Oriented Object Detection
  • [WACV] Improving Object Detection with Inverted Attention
  • [WACV] Propose-and-Attend Single Shot Detector
  • Align Deep Features for Oriented Object Detection
  • AMRNet: Chips Augmentation in Areial Images Object Detection
  • BBRefinement: An universal scheme to improve precision of box object detectors
  • Conditional Convolutions for Instance Segmentation
  • Cross-layer Feature Pyramid Network for Salient Object Detection
  • EAGLE: Large-scale Vehicle Detection Dataset inReal-World Scenarios using Aerial Imagery
  • Extended Feature Pyramid Network for Small Object Detection
  • FeatureNMS: Non-Maximum Suppression by Learning Feature Embeddings
  • Feature Pyramid Grids
  • IterDet: Iterative Scheme for ObjectDetection in Crowded Environments
  • Location-Aware Feature Selection for Scene Text Detection
  • Objects detection for remote sensing images based on polar coordinates
  • Scale-Invariant Multi-Oriented Text Detection in Wild Scene Images
  • Scaled-YOLOv4: Scaling Cross Stage Partial Network

2019

  • [AAAI] Gradient Harmonized Single-stage Detector
  • [AAAI] M2Det: A Single-Shot Object Detector based on Multi-Level Feature Pyramid
  • [BMVC] Rethinking Classification and Localization for Cascade R-CNN
  • [CVPR] Assisted Excitation of Activations: A Learning Technique to Improve Object
  • [CVPR] Borrow from Anywhere Pseudo Multi-modal Object Detection in Thermal Imagery
  • [CVPR] Dual Attention Network for Scene Segmentation
  • [CVPR] Generalized Intersection over Union: A Metric and A Loss for Bounding Box Regression
  • [CVPR] Learning RoI Transformer for Detecting Oriented Objects in Aerial Images
  • [CVPR] Learning Instance Activation Maps for Weakly Supervised Instance Segmentation
  • [CVPR] Libra R-CNN: Towards Balanced Learning for Object Detection
  • [CVPR] Panoptic Segmentation
  • [CVPR] Region Proposal by Guided Anchoring
  • [CVPR] ScratchDet : Training Single-Shot Object Detectors
  • [CVPR] Softer-NMS: Rethinking Bounding Box Regression for Accurate Object Detection
  • [CVPR] Spatial-aware Graph Relation Network for Large-scale Object Detection
  • [CVPR] Weakly Supervised Learning of Instance Segmentation with Inter-pixel Relations
  • [ICCV] Dynamic Multi-scale Filters for Semantic Segmentation
  • [ICCV] EGNet: Edge Guidance Network for Salient Object Detection
  • [ICCV] FCOS: Fully Convolutional One-Stage Object Detection
  • [ICCV] InstaBoost: Boosting Instance Segmentation via Probability Map Guided
  • [ICCV] Gaussian YOLOv3: An Accurate and Fast Object Detector Using Localization Uncertainty for Autonomous Driving
  • [ICCV] Matrix Nets: A New Deep Architecture for Object Detection
  • [ICCV] ThunderNet: Towards Real-time Generic Object Detection
  • [ICCV] Towards More Robust Detection for Small, Cluttered and Rotated Objects
  • [ICCV] Scale-Aware Trident Networks for Object Detection
  • [ICCV] SCRDet: Towards More Robust Detection for Small, Cluttered and Rotated Objects
  • [ICIP] SSSDET: Simple Short and Shallow Network for Resource Efficient Vehicle Detection in Aerial Scenes
  • [ICLR] Approximating CNNs with Bag-of-local-Features models works surprisingly well on ImageNet
  • [ICLR] ImageNet-trained CNNs are biased towards texture: increasing shape bias improves accuracy and robustness
  • [ICLR] Why do deep convolutional networks generalize so poorly to small image transformations?
  • [ICML] How much real data do we actually need: Analyzing object detection performance using synthetic and real data
  • [ICML] Making Convolutional Networks Shift-Invariant Again
  • [ICTAI] Twin Feature Pyramid Networks for Object Detection
  • [IEEE Access] A Real-Time Scene Text Detector with Learned Anchor
  • [IEEE Trans Geosci Remote Sens] CAD-Net: A Context-Aware Detection Network for Objects in Remote Sensing Imagery
  • [IJCAI] Omnidirectional Scene Text Detection with Sequential-free Box Discretization
  • [J. Big Data] A survey on Image Data Augmentation for Deep Learning
  • [NeurIPS] Cascade RPN Delving into High-Quality Region Proposal Network with Adaptive Convolution
  • [NeurIPS] FreeAnchor Learning to Match Anchors for Visual Object Detection
  • A Preliminary Study on Data Augmentation of Deep Learning for Image Classification
  • Bag of Freebies for Training Object Detection Neural Networks
  • Consistent Optimization for Single-Shot Object Detection
  • Deep Learning for 2D and 3D Rotatable Data An Overview of Methods
  • Double-Head RCNN: Rethinking Classification and Localization for Object Detection
  • IENet: Interacting Embranchment One Stage Anchor Free Detector for Orientation Aerial Object Detection
  • IoU-uniform R-CNN: Breaking Through the Limitations of RPN
  • Is Sampling Heuristics Necessary in Training Deep Object Detectors
  • Learning Data Augmentation Strategies for Object Detection
  • Learning from Noisy Anchors for One-stage Object Detection
  • Light-Head R-CNN: In Defense of Two-Stage Object Detector
  • MMDetection: Open MMLab Detection Toolbox and Benchmark
  • Multi-Scale Attention Network for Crowd Counting
  • Natural Adversarial Examples
  • Needles in Haystacks: On Classifying Tiny Objects in Large Images
  • Revisiting Feature Alignment for One-stage Object Detection
  • Ship Detection: An Improved YOLOv3 Method

2018

  • [ACCV] Reverse Densely Connected Feature Pyramid Network for Object Detection
  • [BMVC] Enhancement of SSD by concatenating feature maps for object detection
  • [CVPR] An Analysis of Scale Invariance in Object Detection
  • [CVPR] Cascade R-CNN: Delving into High Quality Object Detection
  • [CVPR] DOTA: A Large-scale Dataset for Object Detection in Aerial Images
  • [CVPR] Path Aggregation Network for Instance Segmentation
  • [CVPR] Pseudo Mask Augmented Object Detection
  • [CVPR] Rotation Sensitive Regression for Oriented Scene Text Detection
  • [CVPR] Scale-Transferable Object Detection
  • [CVPR] Single-Shot Object Detection with Enriched Semantics
  • [CVPR] Single-Shot Refinement Neural Network for Object Detection
  • [CVPR] Squeeze-and-Excitation Networks
  • [CVPR] Weakly Supervised Instance Segmentation using Class Peak Response
  • [ECCV] Acquisition of Localization Confidence for Accurate Object Detection
  • [ECCV] Deep Feature Pyramid Reconfiguration for Object Detection
  • [ECCV] DetNet: A Backbone network for Object Detection
  • [ECCV] Learning to Segment via Cut-and-Paste
  • [ECCV] Modeling Visual Context is Key to Augmenting Object Detection Datasets
  • [ECCV] Receptive Field Block Net for Accurate and Fast Object Detection
  • [ICLR] Multi-Scale Dense Convolutional Networks for Efficient Prediction
  • [ICANN] Further advantages of data augmentation on convolutional neural networks
  • [ISBI] A Novel Focal Tversky loss function with improved Attention U-Net for lesion segmentation
  • [TIP] TextBoxes++: A single-shot oriented scene text detector
  • [TMM] Arbitrary-oriented scene text detection via rotation proposals
  • [IJAC] An Overview of Contour Detection Approaches
  • [IJCV] What Makes Good Synthetic Training Data for Learning Disparity and Optical Flow Estimation?
  • [J Mach Learn Res] Neural Architecture Search: A Survey
  • [Remote Sens.] Automatic Ship Detection of Remote Sensing Images from Google Earth in Complex Scenes Based on Multi-Scale Rotation Dense Feature Pyramid Networks
  • [VISIGRAPP] Learning Transformation Invariant Representations with Weak Supervision
  • [WACV] Understanding Convolution for Semantic Segmentation
  • Data Augmentation by Pairing Samples for Images Classification
  • MDSSD: Multi-scale Deconvolutional Single Shot Detector for Small Objects
  • RAM: Residual Attention Module for Single Image Super-Resolution
  • R2CNN: Rotational Region CNN for Orientation Robust Scene Text Detection

2017

  • [AAAI] Weakly Supervised Semantic Segmentation Using Superpixel Pooling Network
  • [CVPR] Feature Pyramid Networks for Object Detection
  • [CVPR] Not All Pixels Are Equal: Difficulty-Aware Semantic Segmentation via Deep Layer Cascade
  • [CVPR] Oriented Response Networks
  • [CVPR] Simple Does It: Weakly Supervised Instance and Semantic Segmentation
  • [ICCV] Cut, Paste and Learn: Surprisingly Easy Synthesis for Instance Detection
  • [ICCV] Focal Loss for Dense Object Detection
  • [ICCV] Grad-CAM Visual Explanations From Deep Networks via Gradient-Based Localization
  • [ICCV] Single shot scale-invariant face detector
  • [ICCV] Single Shot Text Detector with Regional Attention
  • [ICIP] Rotated region based CNN for ship detection
  • [ICLR] Dataset Augmentationin In Feature Space
  • [ICPRAM] A High Resolution Optical Satellite Image Dataset for Ship Recognition and Some New Baselines
  • [IEEE Acess] Smart Augmentation: Learning an Optimal Data Augmentation Strategy
  • FSSD: Feature Fusion Single Shot Multibox Detector
  • Improved Regularization of Convolutional Neural Networks with Cutout
  • The Effectiveness of Data Augmentation in Image Classification using Deep Learning
  • Tversky loss function for image segmentation using 3D fully convolutional deep networks

2016

  • [CVPR] Learning Deep Features for Discriminative Localization
  • [DICTA] Understanding data augmentation for classification: when to warp?
  • [ECCV] Contextual Priming and Feedback for Faster R-CNN
  • [NIPS] R-FCN: Object Detection via Region-based Fully Convolutional Networks
  • [GRSL] Ship Rotated Bounding Box Space for Ship Extraction From High-Resolution Optical Satellite Images With Complex Backgrounds
  • Beyond Skip Connections: Top-Down Modulation for Object Detection

2015

  • [ICDAR] ICDAR 2015 competition on Robust Reading

2014

  • [CVPR] Scalable Object Detection Using Deep Neural Networks

2012

  • [PAMI] Measuring the Objectness of Image Windows

2009

  • [ICML] Curriculum learning

2000

  • [IJCV] The earth mover's distance as a metric for image retrieval