HyperAI超神经
首页
资讯
最新论文
教程
数据集
百科
SOTA
LLM 模型天梯
GPU 天梯
顶会
开源项目
全站搜索
关于
中文
HyperAI超神经
Toggle sidebar
全站搜索…
⌘
K
首页
SOTA
Source Free Domain Adaptation
Source Free Domain Adaptation On Visda 2017
Source Free Domain Adaptation On Visda 2017
评估指标
Accuracy
评测结果
各个模型在此基准测试上的表现结果
Columns
模型名称
Accuracy
Paper Title
Repository
SFDA2++
89.6
SF(DA)$^2$: Source-free Domain Adaptation Through the Lens of Data Augmentation
RCL
93.2
Empowering Source-Free Domain Adaptation with MLLM-driven Curriculum Learning
NRC
85.9
Exploiting the Intrinsic Neighborhood Structure for Source-free Domain Adaptation
G-SFDA
85.4
Generalized Source-free Domain Adaptation
SHOT++
87.3
Source Data-absent Unsupervised Domain Adaptation through Hypothesis Transfer and Labeling Transfer
SHOT
82.9
Do We Really Need to Access the Source Data? Source Hypothesis Transfer for Unsupervised Domain Adaptation
SFDA2
88.1
SF(DA)$^2$: Source-free Domain Adaptation Through the Lens of Data Augmentation
DaC
87.3
Divide and Contrast: Source-free Domain Adaptation via Adaptive Contrastive Learning
C-SFDA
87.8
C-SFDA: A Curriculum Learning Aided Self-Training Framework for Efficient Source Free Domain Adaptation
0 of 9 row(s) selected.
Previous
Next