Search Results for author: Ningning Ma

Found 8 papers, 6 papers with code

Toward Accurate Camera-based 3D Object Detection via Cascade Depth Estimation and Calibration

no code implementations7 Feb 2024 Chaoqun Wang, Yiran Qin, Zijian Kang, Ningning Ma, Ruimao Zhang

First, a depth estimation (DE) scheme leverages relative depth information to realize the effective feature lifting from 2D to 3D spaces.

3D Object Detection Denoising +6

SupFusion: Supervised LiDAR-Camera Fusion for 3D Object Detection

1 code implementation ICCV 2023 Yiran Qin, Chaoqun Wang, Zijian Kang, Ningning Ma, Zhen Li, Ruimao Zhang

In this paper, we propose a novel training strategy called SupFusion, which provides an auxiliary feature level supervision for effective LiDAR-Camera fusion and significantly boosts detection performance.

3D Object Detection object-detection

RepVGG: Making VGG-style ConvNets Great Again

22 code implementations CVPR 2021 Xiaohan Ding, Xiangyu Zhang, Ningning Ma, Jungong Han, Guiguang Ding, Jian Sun

We present a simple but powerful architecture of convolutional neural network, which has a VGG-like inference-time body composed of nothing but a stack of 3x3 convolution and ReLU, while the training-time model has a multi-branch topology.

Image Classification Semantic Segmentation

Activate or Not: Learning Customized Activation

4 code implementations CVPR 2021 Ningning Ma, Xiangyu Zhang, Ming Liu, Jian Sun

We present a simple, effective, and general activation function we term ACON which learns to activate the neurons or not.

object-detection Object Detection +1

Funnel Activation for Visual Recognition

6 code implementations ECCV 2020 Ningning Ma, Xiangyu Zhang, Jian Sun

We present a conceptually simple but effective funnel activation for image recognition tasks, called Funnel activation (FReLU), that extends ReLU and PReLU to a 2D activation by adding a negligible overhead of spatial condition.

Scene Generation Semantic Segmentation

WeightNet: Revisiting the Design Space of Weight Networks

2 code implementations ECCV 2020 Ningning Ma, Xiangyu Zhang, Jiawei Huang, Jian Sun

WeightNet is easy and memory-conserving to train, on the kernel space instead of the feature space.

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