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Datasets

Greatest papers with code

FEELVOS: Fast End-to-End Embedding Learning for Video Object Segmentation

CVPR 2019 tensorflow/models

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.

SEMANTIC SEGMENTATION SEMI-SUPERVISED VIDEO OBJECT SEGMENTATION VIDEO SEMANTIC SEGMENTATION

Generating Masks from Boxes by Mining Spatio-Temporal Consistencies in Videos

6 Jan 2021visionml/pytracking

This effectively limits the performance and generalization capabilities of existing video segmentation methods.

SEMANTIC SEGMENTATION VIDEO OBJECT SEGMENTATION VIDEO SEGMENTATION VIDEO SEMANTIC SEGMENTATION

Learning What to Learn for Video Object Segmentation

ECCV 2020 visionml/pytracking

This allows us to achieve a rich internal representation of the target in the current frame, significantly increasing the segmentation accuracy of our approach.

FEW-SHOT LEARNING SEMANTIC SEGMENTATION VIDEO OBJECT SEGMENTATION VIDEO SEMANTIC SEGMENTATION YOUTUBE-VOS

Deep Feature Flow for Video Recognition

CVPR 2017 open-mmlab/mmtracking

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 RECOGNITION VIDEO SEMANTIC SEGMENTATION