text: Weakly-Supervised Learning from Videos 
  
  One family of approaches for learning visual perception from videos relies on weakly-supervised guidance from closed 
  captioning, often computed from an ASR transcription of audio data accompanying internet videos. For instance, 
  VideoBERT (Sun et al., 2019; Xu et al., 2021) trains a video encoder to predict masked spans in the textual closed 
  captions. Similarly, VideoCLIP (Xu et al., 2021) trains a video encoder to predict the representation of video 
  captions computed by a text encoder. Follow-up work such as MERLOT (Zellers et al., 2022), VATT (Akbari et al., 
  2021), and InternVideo (Wang et al., 2022) extended VideoCLIP by incorporating additional unsupervised objectives. 