Zobrazeno 1 - 10
of 655
pro vyhledávání: '"Wei Xiaoming"'
Publikováno v:
Guan'gai paishui xuebao, Vol 40, Iss 11, Pp 37-43 (2021)
【Objective】 The objective of this paper is to investigate the influence of nitrogen concentration in nutrient solution on physiological traits of lettuce grown in hydroponic culture. 【Method】 The experiment was conducted in a greenhouse, with
Externí odkaz:
https://doaj.org/article/e4b35ef453204edf949a604ee39e554e
Denoising with a Joint-Embedding Predictive Architecture (D-JEPA), an autoregressive model, has demonstrated outstanding performance in class-conditional image generation. However, the application of next-token prediction in high-resolution text-to-i
Externí odkaz:
http://arxiv.org/abs/2411.14808
Autor:
Guo, Xiuyuan, Xu, Chengqi, Guo, Guinan, Zhu, Feiyu, Cai, Changpeng, Wang, Peizhe, Wei, Xiaoming, Su, Junhao, Gao, Jialin
Currently, training large-scale deep learning models is typically achieved through parallel training across multiple GPUs. However, due to the inherent communication overhead and synchronization delays in traditional model parallelism methods, seamle
Externí odkaz:
http://arxiv.org/abs/2411.12780
Joint-embedding predictive architectures (JEPAs) have shown substantial promise in self-supervised representation learning, yet their application in generative modeling remains underexplored. Conversely, diffusion models have demonstrated significant
Externí odkaz:
http://arxiv.org/abs/2410.03755
Autor:
He, Runze, Ma, Kai, Huang, Linjiang, Huang, Shaofei, Gao, Jialin, Wei, Xiaoming, Dai, Jiao, Han, Jizhong, Liu, Si
Introducing user-specified visual concepts in image editing is highly practical as these concepts convey the user's intent more precisely than text-based descriptions. We propose FreeEdit, a novel approach for achieving such reference-based image edi
Externí odkaz:
http://arxiv.org/abs/2409.18071
Autor:
Li, Hongyu, Hui, Tianrui, Ding, Zihan, Zhang, Jing, Ma, Bin, Wei, Xiaoming, Han, Jizhong, Liu, Si
Panoptic narrative grounding (PNG), whose core target is fine-grained image-text alignment, requires a panoptic segmentation of referred objects given a narrative caption. Previous discriminative methods achieve only weak or coarse-grained alignment
Externí odkaz:
http://arxiv.org/abs/2409.08251
Autor:
Liu, Jiajun, Wang, Yibing, Ma, Hanghang, Wu, Xiaoping, Ma, Xiaoqi, Wei, Xiaoming, Jiao, Jianbin, Wu, Enhua, Hu, Jie
Rapid advancements have been made in extending Large Language Models (LLMs) to Large Multi-modal Models (LMMs). However, extending input modality of LLMs to video data remains a challenging endeavor, especially for long videos. Due to insufficient ac
Externí odkaz:
http://arxiv.org/abs/2408.15542
Autor:
Huang, Shaofei, Ling, Rui, Li, Hongyu, Hui, Tianrui, Tang, Zongheng, Wei, Xiaoming, Han, Jizhong, Liu, Si
In this paper, we propose an Audio-Language-Referenced SAM 2 (AL-Ref-SAM 2) pipeline to explore the training-free paradigm for audio and language-referenced video object segmentation, namely AVS and RVOS tasks. The intuitive solution leverages Ground
Externí odkaz:
http://arxiv.org/abs/2408.15876
Incorporating a temporal dimension into pretrained image diffusion models for video generation is a prevalent approach. However, this method is computationally demanding and necessitates large-scale video datasets. More critically, the heterogeneity
Externí odkaz:
http://arxiv.org/abs/2407.21475
The Gaussian diffusion model, initially designed for image generation, has recently been adapted for 3D point cloud generation. However, these adaptations have not fully considered the intrinsic geometric characteristics of 3D shapes, thereby constra
Externí odkaz:
http://arxiv.org/abs/2407.21428