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DAVIS Challenge 2017
The DAVIS Challenge 2017 benchmark is a dataset for video object segmentation. -
DAVIS Challenge 2018
The DAVIS Challenge 2018 benchmark is a dataset for video object segmentation. -
Memory Aggregation Networks for Efficient Interactive Video Object Segmentation
Interactive video object segmentation (iVOS) aims at efficiently harvesting high-quality segmentation masks of the target object in a video with user interactions. -
Actor and Action (A2D) Dataset
Actor and Action (A2D) dataset is a popular dataset for the actor and action video segmentation task. -
Temporal Scale Aggregation Network for Precise Action Localization in Untrimm...
Temporal action localization is a recently-emerging task, aiming to localize video segments from untrimmed videos that contain speciļ¬c actions. -
Semantic Object Classes in Video
A dataset for semantic object classes in video. -
Video k-net: A Simple, Strong, and Unified Baseline for Video Segmentation
Video k-net: A simple, strong, and unified baseline for video segmentation. -
Tube-Link: A Flexible Cross Tube Framework for Universal Video Segmentation
Video segmentation aims to segment and track every pixel in diverse scenarios accurately. This paper presents Tube-Link, a versatile framework that addresses multiple core tasks... -
Viper dataset
The Viper dataset is a visual perception benchmark to facilitate both low-level and high-level vision tasks, e.g., optical flow and semantic segmentation. It consists of videos...
