Search Results for author: Yi Shan

Found 12 papers, 3 papers with code

ProgressFace: Scale-Aware Progressive Learning for Face Detection

no code implementations ECCV 2020 Jiashu Zhu, Dong Li, Tiantian Han, Lu Tian, Yi Shan

In this work, we propose a novel scale-aware progressive training mechanism to address large scale variations across faces.

Face Detection

3DSFLabelling: Boosting 3D Scene Flow Estimation by Pseudo Auto-labelling

1 code implementation28 Feb 2024 Chaokang Jiang, Guangming Wang, Jiuming Liu, Hesheng Wang, Zhuang Ma, Zhenqiang Liu, Zhujin Liang, Yi Shan, Dalong Du

We present a novel approach from the perspective of auto-labelling, aiming to generate a large number of 3D scene flow pseudo labels for real-world LiDAR point clouds.

Autonomous Driving Data Augmentation +1

Detecting As Labeling: Rethinking LiDAR-camera Fusion in 3D Object Detection

1 code implementation13 Nov 2023 JunJie Huang, Yun Ye, Zhujin Liang, Yi Shan, Dalong Du

3D object Detection with LiDAR-camera encounters overfitting in algorithm development which is derived from the violation of some fundamental rules.

3D Object Detection object-detection

Dual Cross-Attention Learning for Fine-Grained Visual Categorization and Object Re-Identification

no code implementations CVPR 2022 Haowei Zhu, Wenjing Ke, Dong Li, Ji Liu, Lu Tian, Yi Shan

First, we propose global-local cross-attention (GLCA) to enhance the interactions between global images and local high-response regions, which can help reinforce the spatial-wise discriminative clues for recognition.

Ranked #6 on Fine-Grained Image Classification on CUB-200-2011 (using extra training data)

Fine-Grained Image Classification Fine-Grained Visual Categorization

Dynamic Sparse R-CNN

no code implementations CVPR 2022 Qinghang Hong, Fengming Liu, Dong Li, Ji Liu, Lu Tian, Yi Shan

Sparse R-CNN is a recent strong object detection baseline by set prediction on sparse, learnable proposal boxes and proposal features.

object-detection Object Detection

RankDetNet: Delving Into Ranking Constraints for Object Detection

no code implementations CVPR 2021 Ji Liu, Dong Li, Rongzhang Zheng, Lu Tian, Yi Shan

To this end, we comprehensively investigate three types of ranking constraints, i. e., global ranking, class-specific ranking and IoU-guided ranking losses.

3D Object Detection Classification +3

Cross-Dataset Collaborative Learning for Semantic Segmentation in Autonomous Driving

no code implementations21 Mar 2021 Li Wang, Dong Li, Han Liu, Jinzhang Peng, Lu Tian, Yi Shan

Our goal is to train a unified model for improving the performance in each dataset by leveraging information from all the datasets.

3D Semantic Segmentation Autonomous Driving +3

Improving Low-Precision Network Quantization via Bin Regularization

no code implementations ICCV 2021 Tiantian Han, Dong Li, Ji Liu, Lu Tian, Yi Shan

Such bin regularization (BR) mechanism encourages the weight distribution of each quantization bin to be sharp and approximate to a Dirac delta distribution ideally.

Quantization

DNNVM : End-to-End Compiler Leveraging Heterogeneous Optimizations on FPGA-based CNN Accelerators

1 code implementation20 Feb 2019 Yu Xing, Shuang Liang, Lingzhi Sui, Xijie Jia, Jiantao Qiu, Xin Liu, Yushun Wang, Yu Wang, Yi Shan

On the Xilinx ZU2 @330 MHz and ZU9 @330 MHz, we achieve equivalently state-of-the-art performance on our benchmarks by na\"ive implementations without optimizations, and the throughput is further improved up to 1. 26x by leveraging heterogeneous optimizations in DNNVM.

Deep Image: Scaling up Image Recognition

no code implementations13 Jan 2015 Ren Wu, Shengen Yan, Yi Shan, Qingqing Dang, Gang Sun

We present a state-of-the-art image recognition system, Deep Image, developed using end-to-end deep learning.

Data Augmentation

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