5 papers · 1 filter
Motif-Video 2B: Technical Report
Junghwan Lim, Wai Ting Cheung, Minsu Ha +25
Training strong video generation models usually requires massive datasets, large parameter counts, and substantial compute. In this work, we ask whether strong text-to-video qualit…
SynC: Synthetic Image Caption Dataset Refinement with One-to-many Mapping for Zero-shot Image Captioning
Si-Woo Kim, MinJu Jeon, Ye-Chan Kim +3
Zero-shot Image Captioning (ZIC) increasingly utilizes synthetic datasets generated by text-to-image (T2I) models to mitigate the need for costly manual annotation. However, these…
SIDA: Synthetic Image Driven Zero-shot Domain Adaptation
Ye-Chan Kim, SeungJu Cha, Si-Woo Kim +2
Zero-shot domain adaptation is a method for adapting a model to a target domain without utilizing target domain image data. To enable adaptation without target images, existing stu…
ViPCap: Retrieval Text-Based Visual Prompts for Lightweight Image Captioning
Taewhan Kim, Soeun Lee, Si-Woo Kim +1
Recent lightweight image captioning models using retrieved data mainly focus on text prompts. However, previous works only utilize the retrieved text as text prompts, and the visua…
IFCap: Image-like Retrieval and Frequency-based Entity Filtering for Zero-shot Captioning
Soeun Lee, Si-Woo Kim, Taewhan Kim +1
Recent advancements in image captioning have explored text-only training methods to overcome the limitations of paired image-text data. However, existing text-only training methods…