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Found 5 papers, 2 papers with code
Character Grounding and Re-Identification in Story of Videos and Text Descriptions
We address character grounding and re-identification in multiple story-based videos like movies and associated text descriptions.
Cycled Compositional Learning between Images and Text
Since this one-way mapping is highly under-constrained, we couple it with an inverse relation learning with the Correction Network and introduce a cycled relation for given Image We participate in Fashion IQ 2020 challenge and have won the first place with the ensemble of our model.
Transitional Adaptation of Pretrained Models for Visual Storytelling
In this work, we claim that a transitional adaptation task is required between pretraining and finetuning to harmonize the visual encoder and the language model for challenging downstream target tasks like visual storytelling.
Ranked #1 on
Visual Storytelling
on VIST
(ROUGE-L metric, using extra
training data)
Viewpoint-Agnostic Change Captioning With Cycle Consistency
In addition, we propose a cycle consistency module that can potentially improve the performance of any change captioning networks in general by matching the composite feature of the generated caption and before image with the after image feature.
A Joint Sequence Fusion Model for Video Question Answering and Retrieval
We present an approach named JSFusion (Joint Sequence Fusion) that can measure semantic similarity between any pairs of multimodal sequence data (e. g. a video clip and a language sentence).
Ranked #34 on
Video Retrieval
on LSMDC
