Sl_hard_zip -

Specifically curated data points used to train models to distinguish between very similar but incorrect matches (crucial for "Hard" contrastive learning).

The file appears to be a specific dataset or supplement related to the MS-SL (Multi-Scale Semantic Linking) framework, often cited in computer vision and video analysis research. It is frequently associated with a 2022 ACM Multimedia (MM '22) paper titled "Multi-Scale Semantic Linking for Video-Text Retrieval" or similar works from the HuiGuanLab . SL_Hard_zip

Ground truth or processed metadata for datasets like TVR , ActivityNet , or Charades-STA . Specifically curated data points used to train models

While the exact filename "SL_Hard.zip" is common in shared research directories (like Google Drive or Dropbox links found in GitHub repositories), it typically contains: it typically contains: