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20212026
most citedSimple Contrastive Representation Adversarial Learning for NLP Tasks

6 citations · 8 across the 14 of their papers we have counts for

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6 papers · 1 filter

cs.CV2024★ 1 cited

LSVOS Challenge Report: Large-scale Complex and Long Video Object Segmentation

Henghui Ding, Lingyi Hong, Chang Liu +30

Despite the promising performance of current video segmentation models on existing benchmarks, these models still struggle with complex scenes. In this paper, we introduce the 6th…

cs.CV2024

Discriminative Spatial-Semantic VOS Solution: 1st Place Solution for 6th LSVOS

Deshui Miao, Yameng Gu, Xin Li +3

Video object segmentation (VOS) is a crucial task in computer vision, but current VOS methods struggle with complex scenes and prolonged object motions. To address these challenges…

cs.CV2024

Learning Spatial-Semantic Features for Robust Video Object Segmentation

Xin Li, Deshui Miao, Zhenyu He +3

Tracking and segmenting multiple similar objects with distinct or complex parts in long-term videos is particularly challenging due to the ambiguity in identifying target component…

cs.CV2024★ 1 cited

PVUW 2024 Challenge on Complex Video Understanding: Methods and Results

Henghui Ding, Chang Liu, Yunchao Wei +34

Pixel-level Video Understanding in the Wild Challenge (PVUW) focus on complex video understanding. In this CVPR 2024 workshop, we add two new tracks, Complex Video Object Segmentat…

cs.CV2024

1st Place Solution for MOSE Track in CVPR 2024 PVUW Workshop: Complex Video Object Segmentation

Deshui Miao, Xin Li, Zhenyu He +2

Tracking and segmenting multiple objects in complex scenes has always been a challenge in the field of video object segmentation, especially in scenarios where objects are occluded…

cs.CV2024

Spatial-Temporal Multi-level Association for Video Object Segmentation

Deshui Miao, Xin Li, Zhenyu He +2

Existing semi-supervised video object segmentation methods either focus on temporal feature matching or spatial-temporal feature modeling. However, they do not address the issues o…