Papers with YouCookII
Video Paragraph Captioning as a Text Summarization Task (2021.acl-short)
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| Challenge: | Existing methods for video paragraph captioning use ground-truth event segments. |
| Approach: | They propose a video paragraph captioning task that generates coherent paragraphs without ground-truth event segments. |
| Outcome: | The proposed framework outperforms existing methods on two popular datasets. |
Contrastive Video-Language Learning with Fine-grained Frame Sampling (2022.aacl-main)
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| 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. |
Memory-efficient Temporal Moment Localization in Long Videos (2023.eacl-main)
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| Challenge: | Temporal Moment Localization is a multi-modal task that requires understanding the temporal relationships in the entire input video. |
| Approach: | They propose a stochastic sampling module that can process long videos at a constant memory footprint. |
| Outcome: | The proposed model can process videos as long as 18 minutes at a constant memory footprint and achieves faster and faster results than competing models. |
MART: Memory-Augmented Recurrent Transformer for Coherent Video Paragraph Captioning (2020.acl-main)
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| Challenge: | Existing methods for generating paragraph descriptions for videos require a coherent paragraph and a higher level of coherence. |
| Approach: | They propose a new method that generates a summarized memory state from video segments and sentence history to help better predict the next sentence. |
| Outcome: | The proposed method generates more coherent and less repetitive paragraph captions while maintaining relevance to the input video events. |