Video Semantic Segmentation
322 papers with code • 5 benchmarks • 8 datasets
Benchmarks
These leaderboards are used to track progress in Video Semantic Segmentation
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Libraries
Use these libraries to find Video Semantic Segmentation models and implementations
Cityscapes
CamVid
SegTrack-v2
VSPW
MOSE
ODMS
LaRS
Most implemented papers
Make One-Shot Video Object Segmentation Efficient Again
dvl-tum/e-osvos
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NeurIPS 2020
In the semi-supervised setting, the first mask of each object is provided at test time.
Deep Feature Flow for Video Recognition
msracver/Deep-Feature-Flow
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CVPR 2017
Yet, it is non-trivial to transfer the state-of-the-art image recognition networks to videos as per-frame evaluation is too slow and unaffordable.
Video Object Segmentation with Re-identification
lxx1991/VS-ReID
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Specifically, our Video Object Segmentation with Re-identification (VS-ReID) model includes a mask propagation module and a ReID module.
UAVid: A Semantic Segmentation Dataset for UAV Imagery
YeLyuUT/MSDNet
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There already exist several semantic segmentation datasets for comparison among semantic segmentation methods in complex urban scenes, such as the Cityscapes and CamVid datasets, where the side views of the objects are captured with a camera mounted on the driving car.
FEELVOS: Fast End-to-End Embedding Learning for Video Object Segmentation
tensorflow/models
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CVPR 2019
Many of the recent successful methods for video object segmentation (VOS) are overly complicated, heavily rely on fine-tuning on the first frame, and/or are slow, and are hence of limited practical use.
Video Object Segmentation using Space-Time Memory Networks
In our framework, the past frames with object masks form an external memory, and the current frame as the query is segmented using the mask information in the memory.
Physarum Powered Differentiable Linear Programming Layers and Applications
HeatherJiaZG/SuperGlue-pytorch
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We describe our development and show the use of our solver in a video segmentation task and meta-learning for few-shot learning.
Rethinking Space-Time Networks with Improved Memory Coverage for Efficient Video Object Segmentation
hkchengrex/STCN
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NeurIPS 2021
This paper presents a simple yet effective approach to modeling space-time correspondences in the context of video object segmentation.
EPIC-KITCHENS VISOR Benchmark: VIdeo Segmentations and Object Relations
VISOR annotates videos from EPIC-KITCHENS, which comes with a new set of challenges not encountered in current video segmentation datasets.
DVIS-DAQ: Improving Video Segmentation via Dynamic Anchor Queries
Modern video segmentation methods adopt object queries to perform inter-frame association and demonstrate satisfactory performance in tracking continuously appearing objects despite large-scale motion and transient occlusion.
