Papers with VideoCLIP
Contrastive Video-Language Learning with Fine-grained Frame Sampling (2022.aacl-main)
Copied to clipboard
| Challenge: | despite recent progress in video and language representation learning, the weak or sparse correspondence between the two modalities remains a bottleneck. |
| Approach: | They propose a fine-grained contrastive objective for video frame sampling to improve cross-modal correspondence. |
| Outcome: | The proposed approach achieves state-of-the-art performance on YouCookII with long videos. |
VideoCLIP: Contrastive Pre-training for Zero-shot Video-Text Understanding (2021.emnlp-main)
Copied to clipboard
Hu Xu, Gargi Ghosh, Po-Yao Huang, Dmytro Okhonko, Armen Aghajanyan, Florian Metze, Luke Zettlemoyer, Christoph Feichtenhofer
| Challenge: | Recent work adopts a "pre-training + fine-tuning" approach for zero-shot transfer to end tasks without fine- tuning. |
| Approach: | They propose a contrastive approach to pre-train a transformer model for zero-shot video and text understanding without using any labels on downstream tasks. |
| Outcome: | The proposed model outperforms supervised approaches on downstream tasks and outperformed previous approaches. |