Zobrazeno 1 - 10
of 915
pro vyhledávání: '"He Zhenyu"'
Most nuclei are deformed, and these deformations play an important role in various nuclear and astrophysical phenomena. Microscopic nuclear mass models have been developed based on covariant density functional theory to explore exotic nuclear propert
Externí odkaz:
http://arxiv.org/abs/2411.19470
With the development of the internet, recommending interesting products to users has become a highly valuable research topic for businesses. Recommendation systems play a crucial role in addressing this issue. To prevent the leakage of each user's (c
Externí odkaz:
http://arxiv.org/abs/2411.18653
The vision-language tracking task aims to perform object tracking based on various modality references. Existing Transformer-based vision-language tracking methods have made remarkable progress by leveraging the global modeling ability of self-attent
Externí odkaz:
http://arxiv.org/abs/2411.15459
Autor:
Ding, Henghui, Hong, Lingyi, Liu, Chang, Xu, Ning, Yang, Linjie, Fan, Yuchen, Miao, Deshui, Gu, Yameng, Li, Xin, He, Zhenyu, Wang, Yaowei, Yang, Ming-Hsuan, Chai, Jinming, Ma, Qin, Zhang, Junpei, Jiao, Licheng, Liu, Fang, Liu, Xinyu, Zhang, Jing, Zhang, Kexin, Liu, Xu, Li, LingLing, Fang, Hao, Pan, Feiyu, Lu, Xiankai, Zhang, Wei, Cong, Runmin, Tran, Tuyen, Cao, Bin, Zhang, Yisi, Wang, Hanyi, He, Xingjian, Liu, Jing
Despite the promising performance of current video segmentation models on existing benchmarks, these models still struggle with complex scenes. In this paper, we introduce the 6th Large-scale Video Object Segmentation (LSVOS) challenge in conjunction
Externí odkaz:
http://arxiv.org/abs/2409.05847
Video object segmentation (VOS) is a crucial task in computer vision, but current VOS methods struggle with complex scenes and prolonged object motions. To address these challenges, the MOSE dataset aims to enhance object recognition and differentiat
Externí odkaz:
http://arxiv.org/abs/2408.16431
Data Generation Scheme for Thermal Modality with Edge-Guided Adversarial Conditional Diffusion Model
In challenging low light and adverse weather conditions,thermal vision algorithms,especially object detection,have exhibited remarkable potential,contrasting with the frequent struggles encountered by visible vision algorithms. Nevertheless,the effic
Externí odkaz:
http://arxiv.org/abs/2408.03748
Drug-Target binding Affinity (DTA) prediction is essential for drug discovery. Despite the application of deep learning methods to DTA prediction, the achieved accuracy remain suboptimal. In this work, inspired by the recent success of retrieval meth
Externí odkaz:
http://arxiv.org/abs/2407.15202
Deep learning-based multi-view facial capture methods have shown impressive accuracy while being several orders of magnitude faster than a traditional mesh registration pipeline. However, the existing systems (e.g. TEMPEH) are strictly restricted to
Externí odkaz:
http://arxiv.org/abs/2407.10193
Tracking and segmenting multiple similar objects with complex or separate parts in long-term videos is inherently challenging due to the ambiguity of target parts and identity confusion caused by occlusion, background clutter, and long-term variation
Externí odkaz:
http://arxiv.org/abs/2407.07760
In this work, we investigate a typical scenario in code generation where a developer edits existing code in real time and requests a code assistant, e.g., a large language model, to re-predict the next token or next line on the fly. Naively, the LLM
Externí odkaz:
http://arxiv.org/abs/2407.03157