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BDD100K MOTS
The BDD100K MOTS dataset is a subset of the BDD100K dataset, containing 154 videos with annotation for training and validation, and 37 videos for testing. -
Improved Object-Based Style Transfer with Single Deep Network
The proposed approach uses a single deep network of YOLOv8 for both segmentation and style transfer. -
SAM3D Dataset
The SAM3D dataset is a custom dataset created for the SAM3D paper, containing 798 training sequences, 202 validation sequences, and 150 testing sequences. -
SmartMask Dataset
A large-scale dataset consisting of fine-grain amodal segmentation masks for different objects in an input image. -
SHIMRIE dataset
The SHIMRIE dataset is a new dataset for the Object Segmentation from Manipulation Instructions (OSMI) task. It contains 4341 images and 11371 sentences, with a vocabulary size... -
S3DIS and ShapeNetPart
The dataset used for indoor scene segmentation and object part segmentation. -
ShapeStacks
Unsupervised multi-object segmentation using attention and soft-argmax -
ObjectsRoom
Unsupervised multi-object segmentation using attention and soft-argmax -
DAVIS Dataset
The DAVIS dataset contains 60 training sequences and 30 validation sequences, with high-quality densely-annotated segmentation mask annotation for each frame. -
LiveVideos
A large-scale benchmark called LiveVideos for the video object of interest segmentation task. -
Pascal Visual Object Classes (VOC) Challenge
The Pascal Visual Object Classes (VOC) challenge is a benchmark for object detection and segmentation.