-
CFPNet: Channel-wise Feature Pyramid for Real-Time Semantic Segmentation
Real-time semantic segmentation is playing a more important role in computer vision, due to the growing demand for mobile devices and autonomous driving. Therefore, it is very... -
ADE20K Dataset
The ADE20K dataset is a large-scale dataset for semantic segmentation. It contains 20,000 images with 150 semantic categories, with 20,000 images for training, 2,000 images for... -
NYUv2 dataset
The NYUv2 dataset is a large-scale dataset for 3D object recognition and semantic segmentation. It contains 206 test set video sequences with 135 classes. -
The Fishyscapes Benchmark: Measuring Blind Spots in Semantic Segmentation
Anomaly detection in semantic segmentation -
Point Attention Network for Semantic Segmentation of 3D Point Clouds
Convolutional Neural Networks (CNNs) have performed extremely well on data represented by regularly arranged grids such as images. However, directly leveraging the classic... -
SBD dataset
The SBD dataset is a benchmark dataset for semantic segmentation and object detection. -
Dark Zurich
Dark Zurich is a dataset for nighttime semantic segmentation. It contains daytime reference images and nighttime images with corresponding annotations. -
COCO 2017 Dataset
The COCO 2017 Dataset is a large-scale benchmark dataset for object detection, semantic segmentation, and instance segmentation. -
Radar signal deinterleaving dataset
Radar signal deinterleaving dataset based on semantic segmentation with neural network -
CAE v2: Context Autoencoder with CLIP Target
Masked image modeling (MIM) learns visual representation by masking and reconstructing image patches. Applying the reconstruction supervision on the CLIP representation has been... -
Semantic Object Classes in Video
A dataset for semantic object classes in video. -
Spatial Information Guided Convolution for Real-Time RGBD Semantic Segmentation
RGBD semantic segmentation for high-level scene understanding becomes extremely important, benefiting a wide range of applications such as automatic driving, SLAM, and robotics. -
Camvid and Cityscapes datasets
The Camvid and Cityscapes datasets are used for semantic segmentation tasks. -
CamVid Dataset
CamVid dataset is a benchmark dataset for semantic segmentation. It consists of 700 images with 11 object classes. -
Weakly Supervised Semantic Segmentation for Driving Scenes
State-of-the-art techniques in weakly-supervised semantic segmentation (WSSS) using image-level labels exhibit severe performance degradation on driving scene datasets such as... -
Synthia dataset
The Synthia dataset is a driving scenario dataset containing 6 video sequences in 9 different weather environments. -
The Cityscapes Dataset for Semantic Urban Scene Understanding
Cityscapes dataset is a large-scale urban scene dataset containing 30,000 images of street scenes.
