3rd Place Solution for MeViS Track in CVPR 2024 PVUW workshop: Motion Expression guided Video Segmentation

Understand

Referring video object segmentation (RVOS) relies on natural language expressions to segment target objects in video, emphasizing modeling dense text-video relations.

• The current RVOS methods typically use independently pre-trained vision and language models as backbones, resulting in a significant domain gap between video and text.
• In cross-modal feature interaction, text features are only used as query initialization and do not fully utilize important information in the text.
• In this work, we propose using frozen pre-trained vision-language models (VLM) as backbones, with a specific emphasis on enhancing cross-modal feature interaction.