Search Results for author: Kaixiong Gong

Found 9 papers, 8 papers with code

Multimodal Pathway: Improve Transformers with Irrelevant Data from Other Modalities

1 code implementation25 Jan 2024 Yiyuan Zhang, Xiaohan Ding, Kaixiong Gong, Yixiao Ge, Ying Shan, Xiangyu Yue

We propose to improve transformers of a specific modality with irrelevant data from other modalities, e. g., improve an ImageNet model with audio or point cloud datasets.

Text-to-3D Generation with Bidirectional Diffusion using both 2D and 3D priors

no code implementations7 Dec 2023 Lihe Ding, Shaocong Dong, Zhanpeng Huang, Zibin Wang, Yiyuan Zhang, Kaixiong Gong, Dan Xu, Tianfan Xue

Recently, researchers have attempted to improve the genuineness of 3D objects by directly training on 3D datasets, albeit at the cost of low-quality texture generation due to the limited texture diversity in 3D datasets.

Text to 3D Texture Synthesis

Towards Unified and Effective Domain Generalization

1 code implementation16 Oct 2023 Yiyuan Zhang, Kaixiong Gong, Xiaohan Ding, Kaipeng Zhang, Fangrui Lv, Kurt Keutzer, Xiangyu Yue

We propose $\textbf{UniDG}$, a novel and $\textbf{Uni}$fied framework for $\textbf{D}$omain $\textbf{G}$eneralization that is capable of significantly enhancing the out-of-distribution generalization performance of foundation models regardless of their architectures.

Domain Generalization Out-of-Distribution Generalization

Meta-Transformer: A Unified Framework for Multimodal Learning

1 code implementation20 Jul 2023 Yiyuan Zhang, Kaixiong Gong, Kaipeng Zhang, Hongsheng Li, Yu Qiao, Wanli Ouyang, Xiangyu Yue

Multimodal learning aims to build models that can process and relate information from multiple modalities.

Time Series

Improving Transferability for Domain Adaptive Detection Transformers

1 code implementation29 Apr 2022 Kaixiong Gong, Shuang Li, Shugang Li, Rui Zhang, Chi Harold Liu, Qiang Chen

We implement the findings and the alignment modules into our adaptation method, and it benchmarks the DETR-style detector on the domain shift settings.

Object Detection Unsupervised Domain Adaptation

Pareto Domain Adaptation

1 code implementation NeurIPS 2021 Fangrui Lv, Jian Liang, Kaixiong Gong, Shuang Li, Chi Harold Liu, Han Li, Di Liu, Guoren Wang

Domain adaptation (DA) attempts to transfer the knowledge from a labeled source domain to an unlabeled target domain that follows different distribution from the source.

Domain Adaptation Image Classification +2

MetaSAug: Meta Semantic Augmentation for Long-Tailed Visual Recognition

1 code implementation CVPR 2021 Shuang Li, Kaixiong Gong, Chi Harold Liu, Yulin Wang, Feng Qiao, Xinjing Cheng

Real-world training data usually exhibits long-tailed distribution, where several majority classes have a significantly larger number of samples than the remaining minority classes.

Data Augmentation Image Classification +2

Transferable Semantic Augmentation for Domain Adaptation

1 code implementation CVPR 2021 Shuang Li, Mixue Xie, Kaixiong Gong, Chi Harold Liu, Yulin Wang, Wei Li

To remedy this, we propose a Transferable Semantic Augmentation (TSA) approach to enhance the classifier adaptation ability through implicitly generating source features towards target semantics.

Domain Adaptation

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