Search Results for author:
Found 2 papers, 0 papers with code
Deeply Interleaved Two-Stream Encoder for Referring Video Segmentation
To address this task, we first design a two-stream encoder to extract CNN-based visual features and transformer-based linguistic features hierarchically, and a vision-language mutual guidance (VLMG) module is inserted into the encoder multiple times to promote the hierarchical and progressive fusion of multi-modal features.
Ranked #3 on
Referring Expression Segmentation
on J-HMDB
Encoder Fusion Network with Co-Attention Embedding for Referring Image Segmentation
In this work, we propose an encoder fusion network (EFN), which transforms the visual encoder into a multi-modal feature learning network, and uses language to refine the multi-modal features progressively.
