1 citations · 1 across the 1 of their papers we have counts for
8 papers
1st Place Solution for MeViS Track in CVPR 2024 PVUW Workshop: Motion Expression guided Video Segmentation
Mingqi Gao, Jingnan Luo, Jinyu Yang +2
Motion Expression guided Video Segmentation (MeViS), as an emerging task, poses many new challenges to the field of referring video object segmentation (RVOS). In this technical re…
Place Anything into Any Video
Ziling Liu, Jinyu Yang, Mingqi Gao +1
Controllable video editing has demonstrated remarkable potential across diverse applications, particularly in scenarios where capturing or re-capturing real-world videos is either…
Summarization is (Almost) Dead
Xiao Pu, Mingqi Gao, Xiaojun Wan
How well can large language models (LLMs) generate summaries? We develop new datasets and conduct human evaluation experiments to evaluate the zero-shot generation capability of LL…
Learning Cross-Modal Affinity for Referring Video Object Segmentation Targeting Limited Samples
Guanghui Li, Mingqi Gao, Heng Liu +2
Referring video object segmentation (RVOS), as a supervised learning task, relies on sufficient annotated data for a given scene. However, in more realistic scenarios, only minimal…
Reference Matters: Benchmarking Factual Error Correction for Dialogue Summarization with Fine-grained Evaluation Framework
Mingqi Gao, Xiaojun Wan, Jia Su +2
Factuality is important to dialogue summarization. Factual error correction (FEC) of model-generated summaries is one way to improve factuality. Current FEC evaluation that relies…
Is Summary Useful or Not? An Extrinsic Human Evaluation of Text Summaries on Downstream Tasks
Xiao Pu, Mingqi Gao, Xiaojun Wan
Research on automated text summarization relies heavily on human and automatic evaluation. While recent work on human evaluation mainly adopted intrinsic evaluation methods, judgin…