Search Results for author: Tu Zheng

Found 10 papers, 7 papers with code

UniHDA: A Unified and Versatile Framework for Multi-Modal Hybrid Domain Adaptation

no code implementations • 23 Jan 2024 • Hengjia Li, Yang Liu, Yuqi Lin, Zhanwei Zhang, Yibo Zhao, weihang Pan, Tu Zheng, Zheng Yang, Yuchun Jiang, Boxi Wu, Deng Cai

In this paper, we propose UniHDA, a \textbf{unified} and \textbf{versatile} framework for generative hybrid domain adaptation with multi-modal references from multiple domains.

Attribute Domain Adaptation

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Few-shot Hybrid Domain Adaptation of Image Generators

1 code implementation • 30 Oct 2023 • Hengjia Li, Yang Liu, Linxuan Xia, Yuqi Lin, Tu Zheng, Zheng Yang, Wenxiao Wang, Xiaohui Zhong, Xiaobo Ren, Xiaofei He

Concretely, the distance loss blends the attributes of all target domains by reducing the distances from generated images to all target subspaces.

Domain Adaptation Semantic Similarity +1

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NormKD: Normalized Logits for Knowledge Distillation

1 code implementation • 1 Aug 2023 • Zhihao Chi, Tu Zheng, Hengjia Li, Zheng Yang, Boxi Wu, Binbin Lin, Deng Cai

In this paper, we restudy the hyper-parameter temperature and figure out its incapability to distill the knowledge from each sample sufficiently when it is a single value.

Image Classification Knowledge Distillation

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APPT : Asymmetric Parallel Point Transformer for 3D Point Cloud Understanding

no code implementations • 31 Mar 2023 • Hengjia Li, Tu Zheng, Zhihao Chi, Zheng Yang, Wenxiao Wang, Boxi Wu, Binbin Lin, Deng Cai

To tackle these problems, we propose Asymmetric Parallel Point Transformer (APPT).

3D Part Segmentation 3D Semantic Segmentation +2

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CLRNet: Cross Layer Refinement Network for Lane Detection

3 code implementations • CVPR 2022 • Tu Zheng, Yifei HUANG, Yang Liu, Wenjian Tang, Zheng Yang, Deng Cai, Xiaofei He

In this way, we can exploit more contextual information to detect lanes while leveraging local detailed lane features to improve localization accuracy.

Ranked #1 on Lane Detection on LLAMAS

Lane Detection

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Learning to Affiliate: Mutual Centralized Learning for Few-shot Classification

1 code implementation • CVPR 2022 • Yang Liu, Weifeng Zhang, Chao Xiang, Tu Zheng, Deng Cai, Xiaofei He

Few-shot learning (FSL) aims to learn a classifier that can be easily adapted to accommodate new tasks not seen during training, given only a few examples.

Classification Few-Shot Learning

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SCALoss: Side and Corner Aligned Loss for Bounding Box Regression

1 code implementation • 1 Apr 2021 • Tu Zheng, Shuai Zhao, Yang Liu, Zili Liu, Deng Cai

In this paper, we propose Side Overlap~(SO) loss by maximizing the side overlap of two bounding boxes, which puts more penalty for low overlapping bounding box cases.

object-detection Object Detection +1

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DMN4: Few-shot Learning via Discriminative Mutual Nearest Neighbor Neural Network

no code implementations • 15 Mar 2021 • Yang Liu, Tu Zheng, Jie Song, Deng Cai, Xiaofei He

In this paper, we argue that a Mutual Nearest Neighbor (MNN) relation should be established to explicitly select the query descriptors that are most relevant to each task and discard less relevant ones from aggregative clutters in FSL.

Few-Shot Learning