no code implementations • 1 May 2024 • Young Kyun Jang, Dat Huynh, Ashish Shah, Wen-Kai Chen, Ser-Nam Lim
However, we conjecture that this approach has a downside: the projection module distorts the original image representation and confines the resulting composed embeddings to the text-side.
no code implementations • 23 Apr 2024 • Young Kyun Jang, Donghyun Kim, Zihang Meng, Dat Huynh, Ser-Nam Lim
Composed Image Retrieval (CIR) is a task that retrieves images similar to a query, based on a provided textual modification.
1 code implementation • 8 Apr 2024 • Bo He, Hengduo Li, Young Kyun Jang, Menglin Jia, Xuefei Cao, Ashish Shah, Abhinav Shrivastava, Ser-Nam Lim
However, existing LLM-based large multimodal models (e. g., Video-LLaMA, VideoChat) can only take in a limited number of frames for short video understanding.
Ranked #1 on Video Classification on COIN
no code implementations • 6 Dec 2023 • Xuanming Cui, Alejandro Aparcedo, Young Kyun Jang, Ser-Nam Lim
Recent advances in instruction tuning have led to the development of State-of-the-Art Large Multimodal Models (LMMs).
1 code implementation • 16 Dec 2021 • Young Kyun Jang, Geonmo Gu, Byungsoo Ko, Isaac Kang, Nam Ik Cho
To mitigate this issue, data augmentation can be applied during training.
1 code implementation • ICCV 2021 • Young Kyun Jang, Nam Ik Cho
Supervised deep learning-based hash and vector quantization are enabling fast and large-scale image retrieval systems.
no code implementations • 11 Jul 2021 • Young Kyun Jang, Nam Ik Cho
Face image retrieval, which searches for images of the same identity from the query input face image, is drawing more attention as the size of the image database increases rapidly.
2 code implementations • CVPR 2020 • Young Kyun Jang, Nam Ik Cho
Image retrieval methods that employ hashing or vector quantization have achieved great success by taking advantage of deep learning.