8 citations · 37 across the 24 of their papers we have counts for
6 papers · 1 filter
End-to-End Temporal Action Detection with 1B Parameters Across 1000 Frames
Shuming Liu, Chen-Lin Zhang, Chen Zhao +1
Recently, temporal action detection (TAD) has seen significant performance improvement with end-to-end training. However, due to the memory bottleneck, only models with limited sca…
HD-Fusion: Detailed Text-to-3D Generation Leveraging Multiple Noise Estimation
Jinbo Wu, Xiaobo Gao, Xing Liu +5
In this paper, we study Text-to-3D content generation leveraging 2D diffusion priors to enhance the quality and detail of the generated 3D models. Recent progress (Magic3D) in text…
Just a Glimpse: Rethinking Temporal Information for Video Continual Learning
Lama Alssum, Juan Leon Alcazar, Merey Ramazanova +2
Class-incremental learning is one of the most important settings for the study of Continual Learning, as it closely resembles real-world application scenarios. With constrained mem…
Large-capacity and Flexible Video Steganography via Invertible Neural Network
Chong Mou, Youmin Xu, Jiechong Song +3
Video steganography is the art of unobtrusively concealing secret data in a cover video and then recovering the secret data through a decoding protocol at the receiver end. Althoug…
FreeDoM: Training-Free Energy-Guided Conditional Diffusion Model
Jiwen Yu, Yinhuai Wang, Chen Zhao +2
Recently, conditional diffusion models have gained popularity in numerous applications due to their exceptional generation ability. However, many existing methods are training-requ…
A Unified Continual Learning Framework with General Parameter-Efficient Tuning
Qiankun Gao, Chen Zhao, Yifan Sun +4
The "pre-training downstream adaptation" presents both new opportunities and challenges for Continual Learning (CL). Although the recent state-of-the-art in CL is ach…