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cs.CV2026
VIVECaption: A Split Approach to Caption Quality Improvement
Varun Ananth, Baqiao Liu, Haoran Cai
Caption quality has emerged as a critical bottleneck in training high-quality text-to-image (T2I) and text-to-video (T2V) generative models. While visual language models (VLMs) are…
cs.CV2026
Multi-Modal LLM based Image Captioning in ICT: Bridging the Gap Between General and Industry Domain
Lianying Chao, Kai Zhang, Haoran Cai +3
In the information and communications technology (ICT) industry, training a domain-specific large language model (LLM) or constructing a retrieval-augmented generation system requi…
cs.CV2024
HARIVO: Harnessing Text-to-Image Models for Video Generation
Mingi Kwon, Seoung Wug Oh, Yang Zhou +6
We present a method to create diffusion-based video models from pretrained Text-to-Image (T2I) models. Recently, AnimateDiff proposed freezing the T2I model while only training tem…