Zobrazeno 1 - 10
of 22 925
pro vyhledávání: '"ZHAO, Jian"'
Class-incremental learning (CIL) aims to acquire new classes while conserving historical knowledge incrementally. Despite existing pre-trained model (PTM) based methods performing excellently in CIL, it is better to fine-tune them on downstream incre
Externí odkaz:
http://arxiv.org/abs/2411.17766
Autor:
Dai, Guangzhao, Zhao, Jian, Chen, Yuantao, Qin, Yusen, Zhao, Hao, Xie, Guosen, Yao, Yazhou, Shu, Xiangbo, Li, Xuelong
Vision-and-Language Navigation (VLN), where an agent follows instructions to reach a target destination, has recently seen significant advancements. In contrast to navigation in discrete environments with predefined trajectories, VLN in Continuous En
Externí odkaz:
http://arxiv.org/abs/2411.16053
Embedding Space Allocation with Angle-Norm Joint Classifiers for Few-Shot Class-Incremental Learning
Few-shot class-incremental learning (FSCIL) aims to continually learn new classes from only a few samples without forgetting previous ones, requiring intelligent agents to adapt to dynamic environments. FSCIL combines the characteristics and challeng
Externí odkaz:
http://arxiv.org/abs/2411.09250
The Segment Anything Model (SAM) is a cornerstone of image segmentation, demonstrating exceptional performance across various applications, particularly in autonomous driving and medical imaging, where precise segmentation is crucial. However, SAM is
Externí odkaz:
http://arxiv.org/abs/2411.02974
Attention-based architectures have become ubiquitous in time series forecasting tasks, including spatio-temporal (STF) and long-term time series forecasting (LTSF). Yet, our understanding of the reasons for their effectiveness remains limited. This w
Externí odkaz:
http://arxiv.org/abs/2410.24023
Autor:
Luera, Reuben, Rossi, Ryan A., Siu, Alexa, Dernoncourt, Franck, Yu, Tong, Kim, Sungchul, Zhang, Ruiyi, Chen, Xiang, Salehy, Hanieh, Zhao, Jian, Basu, Samyadeep, Mathur, Puneet, Lipka, Nedim
The applications of generative AI have become extremely impressive, and the interplay between users and AI is even more so. Current human-AI interaction literature has taken a broad look at how humans interact with generative AI, but it lacks specifi
Externí odkaz:
http://arxiv.org/abs/2410.22370
StarCraft Multi-Agent Challenge (SMAC) is one of the most commonly used experimental environments in multi-agent reinforcement learning (MARL), where the specific task is to control a set number of allied units to defeat enemy forces. Traditional MAR
Externí odkaz:
http://arxiv.org/abs/2410.16024
Autor:
Min, Chen, Si, Shubin, Wang, Xu, Xue, Hanzhang, Jiang, Weizhong, Liu, Yang, Wang, Juan, Zhu, Qingtian, Zhu, Qi, Luo, Lun, Kong, Fanjie, Miao, Jinyu, Cai, Xudong, An, Shuai, Li, Wei, Mei, Jilin, Sun, Tong, Zhai, Heng, Liu, Qifeng, Zhao, Fangzhou, Chen, Liang, Wang, Shuai, Shang, Erke, Shang, Linzhi, Zhao, Kunlong, Li, Fuyang, Fu, Hao, Jin, Lei, Zhao, Jian, Mao, Fangyuan, Xiao, Zhipeng, Li, Chengyang, Dai, Bin, Zhao, Dawei, Xiao, Liang, Nie, Yiming, Hu, Yu, Li, Xuelong
Research on autonomous driving in unstructured outdoor environments is less advanced than in structured urban settings due to challenges like environmental diversities and scene complexity. These environments-such as rural areas and rugged terrains-p
Externí odkaz:
http://arxiv.org/abs/2410.07701
Concealed object detection (COD) in cluttered scenes is significant for various image processing applications. However, due to that concealed objects are always similar to their background, it is extremely hard to distinguish them. Here, the major ob
Externí odkaz:
http://arxiv.org/abs/2410.06842
Autor:
Chen, Yushen, Niu, Zhikang, Ma, Ziyang, Deng, Keqi, Wang, Chunhui, Zhao, Jian, Yu, Kai, Chen, Xie
This paper introduces F5-TTS, a fully non-autoregressive text-to-speech system based on flow matching with Diffusion Transformer (DiT). Without requiring complex designs such as duration model, text encoder, and phoneme alignment, the text input is s
Externí odkaz:
http://arxiv.org/abs/2410.06885