Kaicheng Yu | DeepAI

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∙ 09/11/2023

FusionFormer: A Multi-sensory Fusion in Bird's-Eye-View and Temporal Consistent Transformer for 3D Objection

Multi-sensor modal fusion has demonstrated strong advantages in 3D objec...

0 Chunyong Hu, et al. ∙

∙ 08/02/2023

FusionAD: Multi-modality Fusion for Prediction and Planning Tasks of Autonomous Driving

Building a multi-modality multi-task neural network toward accurate and ...

0 Tengju Ye, et al. ∙

∙ 07/24/2023

Dyn-E: Local Appearance Editing of Dynamic Neural Radiance Fields

Recently, the editing of neural radiance fields (NeRFs) has gained consi...

0 Shangzhan Zhang, et al. ∙

∙ 04/20/2023

LiDAR-NeRF: Novel LiDAR View Synthesis via Neural Radiance Fields

We introduce a new task, novel view synthesis for LiDAR sensors. While t...

0 Tang Tao, et al. ∙

∙ 03/15/2023

BEVHeight: A Robust Framework for Vision-based Roadside 3D Object Detection

While most recent autonomous driving system focuses on developing percep...

0 Lei Yang, et al. ∙

∙ 02/14/2023

Painting 3D Nature in 2D: View Synthesis of Natural Scenes from a Single Semantic Mask

We introduce a novel approach that takes a single semantic mask as input...

0 Shangzhan Zhang, et al. ∙

∙ 11/18/2022

α DARTS Once More: Enhancing Differentiable Architecture Search by Masked Image Modeling

Differentiable architecture search (DARTS) has been a mainstream directi...

0 Guo Bicheng, Brandon, et al. ∙

∙ 10/16/2022

Learning Self-Regularized Adversarial Views for Self-Supervised Vision Transformers

Automatic data augmentation (AutoAugment) strategies are indispensable i...

3 Tao Tang, et al. ∙

∙ 05/30/2022

Benchmarking the Robustness of LiDAR-Camera Fusion for 3D Object Detection

There are two critical sensors for 3D perception in autonomous driving, ...

0 Kaicheng Yu, et al. ∙

∙ 05/27/2022

BEVFusion: A Simple and Robust LiDAR-Camera Fusion Framework

Fusing the camera and LiDAR information has become a de-facto standard f...

0 Tingting Liang, et al. ∙

∙ 01/31/2022

NAS-Bench-Suite: NAS Evaluation is (Now) Surprisingly Easy

The release of tabular benchmarks, such as NAS-Bench-101 and NAS-Bench-2...

0 Yash Mehta, et al. ∙

∙ 10/04/2021

An Analysis of Super-Net Heuristics in Weight-Sharing NAS

Weight sharing promises to make neural architecture search (NAS) tractab...

0 Kaicheng Yu, et al. ∙

∙ 04/12/2021

Landmark Regularization: Ranking Guided Super-Net Training in Neural Architecture Search

Weight sharing has become a de facto standard in neural architecture sea...

0 Kaicheng Yu, et al. ∙

∙ 03/09/2020

How to Train Your Super-Net: An Analysis of Training Heuristics in Weight-Sharing NAS

Weight sharing promises to make neural architecture search (NAS) tractab...

0 Kaicheng Yu, et al. ∙

∙ 06/11/2019

Recurrent U-Net for Resource-Constrained Segmentation

State-of-the-art segmentation methods rely on very deep networks that ar...

0 Wei Wang, et al. ∙

∙ 02/21/2019

Overcoming Multi-Model Forgetting

We identify a phenomenon, which we refer to as multi-model forgetting, t...

0 Yassine Benyahia, et al. ∙

∙ 02/21/2019

Evaluating the Search Phase of Neural Architecture Search

Neural Architecture Search (NAS) aims to facilitate the design of deep n...

0 Christian Sciuto, et al. ∙

∙ 11/27/2018

Beyond One Glance: Gated Recurrent Architecture for Hand Segmentation

As mixed reality is gaining increased momentum, the development of effec...

0 Wei Wang, et al. ∙

∙ 01/23/2018

Statistically Motivated Second Order Pooling

Second-order pooling, a.k.a. bilinear pooling, has proven effective for ...

0 Kaicheng Yu, et al. ∙

∙ 03/20/2017

Second-order Convolutional Neural Networks

Convolutional Neural Networks (CNNs) have been successfully applied to m...

0 Kaicheng Yu, et al. ∙

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