MaskLab: Instance Segmentation by Refining Object Detection with Semantic and Direction Features
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- Type
- preprint
- Published
- 2017-12-13
- Cited by
- 368
- References
- 85
- Access
- Open access
- OpenAlex
- https://openalex.org/W2774692246
- Semantic Scholar
- https://api.semanticscholar.org/CorpusID:21557197
Keywords
Segmentation, Computer science, Artificial intelligence, Benchmark (surveying), Object (grammar)
References
- Monocular Object Instance Segmentation and Depth Ordering with CNNs
- Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks
- Learning to Segment Object Candidates
- You Only Look Once: Unified, Real-Time Object Detection
- Weakly- and Semi-Supervised Learning of a DCNN for Semantic Image Segmentation
- Scalable, High-Quality Object Detection
- Distilling the Knowledge in a Neural Network
- Fully convolutional networks for semantic segmentation
- Predicting Depth, Surface Normals and Semantic Labels with a Common Multi-scale Convolutional Architecture
- Convolutional feature masking for joint object and stuff segmentation
- Multi-instance object segmentation with occlusion handling
- Object Detection via a Multi-region and Semantic Segmentation-Aware CNN Model
- Hypercolumns for object segmentation and fine-grained localization
- Modeling local and global deformations in Deep Learning: Epitomic convolution, Multiple Instance Learning, and sliding window detection
- segDeepM: Exploiting segmentation and context in deep neural networks for object detection
- Fast High‐Dimensional Filtering Using the Permutohedral Lattice
- Multiscale Combinatorial Grouping
- CPMC: Automatic Object Segmentation Using Constrained Parametric Min-Cuts
- Scalable Object Detection Using Deep Neural Networks
- Fast image scanning with deep max-pooling convolutional neural networks
Cited by
- PersonLab: Person Pose Estimation and Instance Segmentation with a Bottom-Up, Part-Based, Geometric Embedding Model
- Box2Pix: Single-Shot Instance Segmentation by Assigning Pixels to Object Boxes
- Semantic Instance Meets Salient Object: Study on Video Semantic Salient Instance Segmentation
- Actor-Action Semantic Segmentation with Region Masks
- Bounding Box Embedding for Single Shot Person Instance Segmentation
- LUCSS: Language-based User-customized Colourization of Scene Sketches
- A Baseline for General Music Object Detection with Deep Learning
- Searching for Efficient Multi-Scale Architectures for Dense Image Prediction
- Deep Convolutional Neural Networks for Automated Characterization of Arctic Ice-Wedge Polygons in Very High Spatial Resolution Aerial Imagery
- The ApolloScape Open Dataset for Autonomous Driving and Its Application
- A weakly supervised approach for estimating spatial density functions from high-resolution satellite imagery
- A Mask Regional Convolutional Neural Network Model for Segmenting Real Time Traffic Images
- Efficient Video Understanding via Layered Multi Frame-Rate Analysis
- AttentionMask: Attentive, Efficient Object Proposal Generation Focusing on Small Objects
- One-Shot Instance Segmentation
- TextField: Learning a Deep Direction Field for Irregular Scene Text Detection
- Learning to Fuse Things and Stuff
- DeepFlux for Skeletons in the Wild
- Weakly Supervised Instance Segmentation Using Hybrid Networks
- Segmentation of Instances by Hashing
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