activity
20202024
most citedEfficient Long-Short Temporal Attention Network for Unsupervised Video Object Segmentation

30 citations · 56 across the 5 of their papers we have counts for

collaborators

7 papers

cs.CV2024

Pseudo-labeling with Keyword Refining for Few-Supervised Video Captioning

Ping Li, Tao Wang, Xinkui Zhao +2

Video captioning generate a sentence that describes the video content. Existing methods always require a number of captions (\eg, 10 or 20) per video to train the model, which is q…

cs.CV20231 cited

Pair-wise Layer Attention with Spatial Masking for Video Prediction

Ping Li, Chenhan Zhang, Zheng Yang +2

Video prediction yields future frames by employing the historical frames and has exhibited its great potential in many applications, e.g., meteorological prediction, and autonomous…

cs.CV2023

Adversarial Attacks on Video Object Segmentation with Hard Region Discovery

Ping Li, Yu Zhang, Li Yuan +3

Video object segmentation has been applied to various computer vision tasks, such as video editing, autonomous driving, and human-robot interaction. However, the methods based on d…

cs.CV2023

Triple-View Knowledge Distillation for Semi-Supervised Semantic Segmentation

Ping Li, Junjie Chen, Li Yuan +2

To alleviate the expensive human labeling, semi-supervised semantic segmentation employs a few labeled images and an abundant of unlabeled images to predict the pixel-level label m…

cs.CV202318 cited

Fully Transformer-Equipped Architecture for End-to-End Referring Video Object Segmentation

Ping Li, Yu Zhang, Li Yuan +1

Referring Video Object Segmentation (RVOS) requires segmenting the object in video referred by a natural language query. Existing methods mainly rely on sophisticated pipelines to…

cs.CV202330 cited

Efficient Long-Short Temporal Attention Network for Unsupervised Video Object Segmentation

Ping Li, Yu Zhang, Li Yuan +3

Unsupervised Video Object Segmentation (VOS) aims at identifying the contours of primary foreground objects in videos without any prior knowledge. However, previous methods do not…