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20222024
most citedFERV39k: A Large-Scale Multi-Scene Dataset for Facial Expression Recognition in Videos

6 citations · 9 across the 4 of their papers we have counts for

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5 papers · 1 filter

cs.CV20241 cited

LVOS: A Benchmark for Large-scale Long-term Video Object Segmentation

Lingyi Hong, Zhongying Liu, Wenchao Chen +9

Video object segmentation (VOS) aims to distinguish and track target objects in a video. Despite the excellent performance achieved by off-the-shell VOS models, existing VOS benchm…

cs.CV2024

ClickVOS: Click Video Object Segmentation

Pinxue Guo, Lingyi Hong, Xinyu Zhou +7

Video Object Segmentation (VOS) task aims to segment objects in videos. However, previous settings either require time-consuming manual masks of target objects at the first frame d…

cs.CV2023

SimulFlow: Simultaneously Extracting Feature and Identifying Target for Unsupervised Video Object Segmentation

Lingyi Hong, Wei Zhang, Shuyong Gao +2

Unsupervised video object segmentation (UVOS) aims at detecting the primary objects in a given video sequence without any human interposing. Most existing methods rely on two-strea…

cs.CV2023

PanoVOS: Bridging Non-panoramic and Panoramic Views with Transformer for Video Segmentation

Shilin Yan, Xiaohao Xu, Renrui Zhang +4

Panoramic videos contain richer spatial information and have attracted tremendous amounts of attention due to their exceptional experience in some fields such as autonomous driving…

cs.CV20226 cited

FERV39k: A Large-Scale Multi-Scene Dataset for Facial Expression Recognition in Videos

Yan Wang, Yixuan Sun, Yiwen Huang +5

Current benchmarks for facial expression recognition (FER) mainly focus on static images, while there are limited datasets for FER in videos. It is still ambiguous to evaluate whet…