Coherent Multi-Sentence Video Description with Variable Level of Detail
Table 4: Evaluating detailed descriptions. BLEU@4 in %. Human judgments from 1-5, where 5 is best.
['PER SENTENCE', 'PER SENTENCE', 'PER DESCRIPTION', 'PER DESCRIPTION Human judgments', 'PER DESCRIPTION Human judgments', 'PER DESCRIPTION Human judgments']
Judges rate especially the readability much higher (+0.8) which is due to our increased consistency introduced by the dish node. Also correctness (+0.3) and relevance (+0.2) is rated higher, and the BLEU score improves by 1.9% and 8.1%. To estimate the effect of our hand centric features we evaluate our SMT without them, which reaches a BLEU score of 24.1% (-1.0%) per sentence and 61.1% (-2.7%) for full descriptions. This indicates that the suggested features have a strong effect not only on the visual recognition performance but also on the quality of our descriptions. Again all scores increase. Most notably the BLEU@4 score by 2.3% and readability by 0.3. We can further improve readability to 3.8 by applying linguistic post-processing to the description (see Sec. This indicates the good quality of our segmentation. Third, surprisingly the relevance slightly improves for our approaches by 0.1/0.2. This might be due to our background classifier which removes unimportant segments.