Zobrazeno 1 - 10
of 504
pro vyhledávání: '"Li, Xinhao"'
Autor:
Zeng, Xiangyu, Li, Kunchang, Wang, Chenting, Li, Xinhao, Jiang, Tianxiang, Yan, Ziang, Li, Songze, Shi, Yansong, Yue, Zhengrong, Wang, Yi, Wang, Yali, Qiao, Yu, Wang, Limin
Multimodal Large Language Models (MLLMs) have demonstrated impressive performance in short video understanding. However, understanding long-form videos still remains challenging for MLLMs. This paper proposes TimeSuite, a collection of new designs to
Externí odkaz:
http://arxiv.org/abs/2410.19702
Neural radiance fields (NeRFs) are a deep learning technique that can generate novel views of 3D scenes using sparse 2D images from different viewing directions and camera poses. As an extension of conventional NeRFs in underwater environment, where
Externí odkaz:
http://arxiv.org/abs/2407.08154
With the growth of high-quality data and advancement in visual pre-training paradigms, Video Foundation Models (VFMs) have made significant progress recently, demonstrating their remarkable performance on traditional video understanding benchmarks. H
Externí odkaz:
http://arxiv.org/abs/2407.06491
Autor:
Sun, Yu, Li, Xinhao, Dalal, Karan, Xu, Jiarui, Vikram, Arjun, Zhang, Genghan, Dubois, Yann, Chen, Xinlei, Wang, Xiaolong, Koyejo, Sanmi, Hashimoto, Tatsunori, Guestrin, Carlos
Self-attention performs well in long context but has quadratic complexity. Existing RNN layers have linear complexity, but their performance in long context is limited by the expressive power of their hidden state. We propose a new class of sequence
Externí odkaz:
http://arxiv.org/abs/2407.04620
Autor:
Chen, Tingwei, Wang, Yantao, Chen, Hanzhi, Zhao, Zijian, Li, Xinhao, Piovesan, Nicola, Zhu, Guangxu, Shi, Qingjiang
The introduction of fifth-generation (5G) radio technology has revolutionized communications, bringing unprecedented automation, capacity, connectivity, and ultra-fast, reliable communications. However, this technological leap comes with a substantia
Externí odkaz:
http://arxiv.org/abs/2406.16929
Autor:
Li, Xinhao
Batteries play a pivotal role in the modern world, powering everything from portable electronics to electric vehicles, and are critical in the shift towards renewable energy sources by enabling efficient energy storage. This thesis presents new compu
Autor:
Wang, Yi, Li, Kunchang, Li, Xinhao, Yu, Jiashuo, He, Yinan, Wang, Chenting, Chen, Guo, Pei, Baoqi, Yan, Ziang, Zheng, Rongkun, Xu, Jilan, Wang, Zun, Shi, Yansong, Jiang, Tianxiang, Li, Songze, Zhang, Hongjie, Huang, Yifei, Qiao, Yu, Wang, Yali, Wang, Limin
We introduce InternVideo2, a new family of video foundation models (ViFM) that achieve the state-of-the-art results in video recognition, video-text tasks, and video-centric dialogue. Our core design is a progressive training approach that unifies th
Externí odkaz:
http://arxiv.org/abs/2403.15377
Addressing the dual challenges of local redundancy and global dependencies in video understanding, this work innovatively adapts the Mamba to the video domain. The proposed VideoMamba overcomes the limitations of existing 3D convolution neural networ
Externí odkaz:
http://arxiv.org/abs/2403.06977
Autor:
Komurcuoglu, Cem, Xiao, Yunhao, Li, Xinhao, Rodriguez-Lopez, Joaquin, Li, Zheng, West, Alan C., Urban, Alexander
Although LiNiO$_2$ is chemically similar to LiCoO$_2$ and offers a nearly identical theoretical capacity, LiNiO$_2$ and related Co-free Ni-rich cathode materials suffer from degradation during electrochemical cycling that has prevented practical use
Externí odkaz:
http://arxiv.org/abs/2401.05983
Autor:
Xu, Jing, Horn, Connor, Jiang, Yu, Li, Xinhao, Rosenmann, Daniel, Han, Xu, Levy, Miguel, Guha, Supratik, Zhang, Xufeng
Yttrium iron garnet (YIG) magnonics has sparked extensive research interests toward harnessing magnons (quasiparticles of collective spin excitation) for signal processing. In particular, YIG magnonics-based hybrid systems exhibit great potentials fo
Externí odkaz:
http://arxiv.org/abs/2312.10660