Search Results for author: Yifan Pu

Found 11 papers, 7 papers with code

Improving Detection in Aerial Images by Capturing Inter-Object Relationships

no code implementations5 Apr 2024 Botao Ren, Botian Xu, Yifan Pu, Jingyi Wang, Zhidong Deng

In many image domains, the spatial distribution of objects in a scene exhibits meaningful patterns governed by their semantic relationships.

GRA: Detecting Oriented Objects through Group-wise Rotating and Attention

no code implementations17 Mar 2024 Jiangshan Wang, Yifan Pu, Yizeng Han, Jiayi Guo, Yiru Wang, Xiu Li, Gao Huang

GRA can adaptively capture fine-grained features of objects with diverse orientations, comprising two key components: Group-wise Rotating and Group-wise Attention.

Object object-detection +2

LLM Agents for Psychology: A Study on Gamified Assessments

no code implementations19 Feb 2024 Qisen Yang, Zekun Wang, Honghui Chen, Shenzhi Wang, Yifan Pu, Xin Gao, Wenhao Huang, Shiji Song, Gao Huang

Psychological measurement is essential for mental health, self-understanding, and personal development.

Smooth Diffusion: Crafting Smooth Latent Spaces in Diffusion Models

1 code implementation7 Dec 2023 Jiayi Guo, Xingqian Xu, Yifan Pu, Zanlin Ni, Chaofei Wang, Manushree Vasu, Shiji Song, Gao Huang, Humphrey Shi

Specifically, we introduce Step-wise Variation Regularization to enforce the proportion between the variations of an arbitrary input latent and that of the output image is a constant at any diffusion training step.

Fine-grained Recognition with Learnable Semantic Data Augmentation

1 code implementation1 Sep 2023 Yifan Pu, Yizeng Han, Yulin Wang, Junlan Feng, Chao Deng, Gao Huang

Since images belonging to the same meta-category usually share similar visual appearances, mining discriminative visual cues is the key to distinguishing fine-grained categories.

Data Augmentation Fine-Grained Image Recognition +2

Latency-aware Unified Dynamic Networks for Efficient Image Recognition

1 code implementation30 Aug 2023 Yizeng Han, Zeyu Liu, Zhihang Yuan, Yifan Pu, Chaofei Wang, Shiji Song, Gao Huang

Dynamic computation has emerged as a promising avenue to enhance the inference efficiency of deep networks.


Dynamic Perceiver for Efficient Visual Recognition

1 code implementation ICCV 2023 Yizeng Han, Dongchen Han, Zeyu Liu, Yulin Wang, Xuran Pan, Yifan Pu, Chao Deng, Junlan Feng, Shiji Song, Gao Huang

Early exits are placed exclusively within the classification branch, thus eliminating the need for linear separability in low-level features.

Action Recognition Classification +4

Adaptive Rotated Convolution for Rotated Object Detection

1 code implementation ICCV 2023 Yifan Pu, Yiru Wang, Zhuofan Xia, Yizeng Han, Yulin Wang, Weihao Gan, Zidong Wang, Shiji Song, Gao Huang

In our ARC module, the convolution kernels rotate adaptively to extract object features with varying orientations in different images, and an efficient conditional computation mechanism is introduced to accommodate the large orientation variations of objects within an image.

Ranked #3 on Object Detection In Aerial Images on DOTA (using extra training data)

Object object-detection +2

Latency-aware Spatial-wise Dynamic Networks

2 code implementations12 Oct 2022 Yizeng Han, Zhihang Yuan, Yifan Pu, Chenhao Xue, Shiji Song, Guangyu Sun, Gao Huang

The latency prediction model can efficiently estimate the inference latency of dynamic networks by simultaneously considering algorithms, scheduling strategies, and hardware properties.

Image Classification Instance Segmentation +4

Learning to Weight Samples for Dynamic Early-exiting Networks

1 code implementation17 Sep 2022 Yizeng Han, Yifan Pu, Zihang Lai, Chaofei Wang, Shiji Song, Junfen Cao, Wenhui Huang, Chao Deng, Gao Huang

Intuitively, easy samples, which generally exit early in the network during inference, should contribute more to training early classifiers.


Cannot find the paper you are looking for? You can Submit a new open access paper.