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 • 20 Nov 2022 • Peirong Liu, Rui Wang, Pengchuan Zhang, Omid Poursaeed, Yipin Zhou, Xuefei Cao, Sreya Dutta Roy, Ashish Shah, Ser-Nam Lim
We propose TrIVD (Tracking and Image-Video Detection), the first framework that unifies image OD, video OD, and MOT within one end-to-end model.
1 code implementation • 2 Dec 2021 • Zihang Meng, David Yang, Xuefei Cao, Ashish Shah, Ser-Nam Lim
Our work in this paper overcomes this by harvesting objects corresponding to a given sentence from the training set, even if they don't belong to the same image.
no code implementations • 9 Oct 2021 • Peirong Liu, Rui Wang, Xuefei Cao, Yipin Zhou, Ashish Shah, Ser-Nam Lim
Key findings are twofold: (1) by capturing the motion transfer with an ordinary differential equation (ODE), it helps to regularize the motion field, and (2) by utilizing the source image itself, we are able to inpaint occluded/missing regions arising from large motion changes.
no code implementations • 16 Nov 2019 • Xuefei Cao, Bor-Chun Chen, Ser-Nam Lim
In this work, we propose to generate pseudo-labels for deep metric learning directly from clustering assignment and we introduce unsupervised deep metric learning (UDML) regularized by a self-supervision (SS) task.