Video Title Generation
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1 Video Title Generation Kuo-Hao Zeng! NTHU EE! Tseng-Hung Chen! NTHU EE! Juan Carlos Niebles! Stanford CS! Min Sun! NTHU EE! Present at!
2 Motivation VSLab Non-edited! No description (e.g., video title)! Never Watched! Again!
3 VSLab What If? Detect the highlight moment! Generate a description of the highlight! Bmx rider gets hit by scooter at park Pretty Good Title! Video Title Generation
4 Title vs. Caption Catchy! Describing the most salient event (Highlight)! Title (most salient event): Bmx rider gets hit by scooter at park 1"second"short"highlight" 1"second"short"highlight" 44"seconds"long"video" 1"second"short"highlight" 44"seconds"long"video" Captions: A man riding on bike. A man does a stunt on a bmx bike. Generic! Describing a video as a whole!
5 Related Work VSLab Rohrbach et al. The long-short story of movie description. GCPR 15! S2VT! SA! Venugopalan et al. Sequence to Sequence Video to Text, ICCV'15. Yao et al. Describing Videos by Exploiting Temporal Structure, ICCV'15 Pan et al. Jointly modeling embedding and translation to bridge video and language. CVPR 16! Pan et al. Hierarchical recurrent neural encoder for video representation with application to captioning. CVPR 16! Yu et al. Video paragraph captioning using hierarchical recurrent neural networks. CVPR 16!
6 VSLab Video Title Generation Describing the most salient event (Highlight)! Catchy!
7 VSLab Highlight Sensitive Describing the most salient event (highlight)! - Unknown highlight location in training!
8 VSLab Highlight Sensitive Describing the most salient event (highlight)! - Unknown highlight location in training!! Train!!
9 VSLab Highlight Sensitive Describing the most salient event (Highlight)! - Unknown Highlight Location in Training!! Train!!
10 VSLab Highlight Sensitive Describing the most salient event (Highlight)! - Unknown Highlight Location in Training!! Train!!
11 !! VSLab Video Title Generation Describing the most salient event (Highlight)! Catchy (Diverse)!!! Web!!!
12 VSLab Sentence Augmentation Describing the most salient event (Highlight)! Catchy (Diverse)!
13 Video Title in the Wild (VTW) Dataset VSLab YouTube channels curating! viral videos! editor-verified video titles!
14 Video Title in the Wild VSLab (VTW) Dataset Title: Kitten Falls off Dresser! Description: Just as this kitten started to get the nerve up to leap from the top of a dresser to the floor, it struggled with its balance and fell off.! Title: Hungry Baby Elephant Starts Tug of War with Tourist's Scarf! Description: This baby Indian elephant may look docile, but this tourist quickly learns otherwise it's really a scarfscarfing machine! While petting the elephant's trunk and sporadically turning to pose for her videographer husband, the woman suddenly finds herself in a fight for her scarf, now the subject of a tug-of-war match between herself and this hungry, hungry elephant.!
15 VSLab Video Title in the Wild (VTW) Dataset Videos: 14100(training) (testing) (validation)! Titles: 14100(training) (testing) (validation)!
16 Details VSLab Initial weak highlight detector (1000 training videos)! Augment from Web (3546 sentences)!
17 Result on VTW VSLab
18 Result on VTW VSLab
19 Result on VTW VSLab
20 Result on VTW VSLab
21 Result on VTW VSLab
22 Result on M-VAD VSLab Augment from MPII dataset! METERO: S2VT+Aug 7.1% vs. S2VT 6.7%! Torabi, A., Pal, C.J., Larochelle, H., Courville, A.C.: Using descriptive video services to create a large data source for video annotation research. In: arxiv: ! Rohrbach, A., Rohrbach, M., Tandon, N., Schiele, B.: A dataset for movie description. In: CVPR 15!
23
24 Thanks!
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