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ICCV2023 paper list

ICCV2023结果陆续都出来了,收到了很多朋友中稿的消息,ICCV 2023今年一共收录 2100多篇,自动驾驶之心也第一时间进行了跟进,将已确定中稿的工作分享给大家,后面将会持续更新!

后面将会按照3D目标检测、BEV、协同感知、语义分割、点云、SLAM、大模型、NeRF、端到端、多模态融合等多个方向罗列!

如果您的工作也需要被收录,欢迎提交Issue,或者联系邮箱[email protected],我们会及时收录!

本内容由自公众号【自动驾驶之心】 团队整理,自动驾驶之心建立了一系列技术交流群,面向自动驾驶与AI领域,包括:目标检测、语义分割、全景分割、实例分割、车道线、目标跟踪、3D目标检测、多模态感知、BEV感知、Occupancy、多传感器融合、多传感器标定、transformer、大模型、点云处理、端到端自动驾驶、SLAM、光流估计、深度估计、轨迹预测、高精地图、NeRF、规划控制、模型部署落地、自动驾驶仿真测试、产品经理、硬件配置、AI求职交流等

如果您有需要,欢迎加入自动驾驶之心:技术交流群

1)OCC感知

SurroundOcc: Multi-Camera 3D Occupancy Prediction for Autonomous Driving

OccNet: Scene as Occupancy

OccFormer: Dual-path Transformer for Vision-based 3D Semantic Occupancy Prediction

OpenOccupancy: A Large Scale Benchmark for Surrounding Semantic Occupancy Perception

2) 端到端自动驾驶

VAD: Vectorized Scene Representation for Efficient Autonomous Driving

DriveAdapter: New Paradigm for End-to-End Autonomous Driving to Alleviate Causal Confusion

3)协同感知

Among Us: Adversarially Robust Collaborative Perception by Consensus

HM-ViT: Hetero-modal Vehicle-to-Vehicle Cooperative perception with vision transformer

Optimizing the Placement of Roadside LiDARs for Autonomous Driving

待更新!

UMC: A Unified Bandwidth-efficient and Multi-resolution based Collaborative Perception Framework

ADAPT: Efficient Multi-Agent Trajectory Prediction with Adaptation

CORE: Cooperative Reconstruction for Multi-Agent Perception

4)3D目标检测

PETRv2: A Unified Framework for 3D Perception from Multi-Camera Images

StreamPETR: Exploring Object-Centric Temporal Modeling for Efficient Multi-View 3D Object Detection

Cross Modal Transformer: Towards Fast and Robust 3D Object Detection

DQS3D: Densely-matched Quantization-aware Semi-supervised 3D Detection

SparseFusion: Fusing Multi-Modal Sparse Representations for Multi-Sensor 3D Object Detection

MetaBEV: Solving Sensor Failures for BEV Detection and Map Segmentation

Temporal Enhanced Training of Multi-view 3D Object Detector via Historical Object Prediction

Revisiting Domain-Adaptive 3D Object Detection by Reliable, Diverse and Class-balanced Pseudo-Labeling

Learning from Noisy Data for Semi-Supervised 3D Object Detection

SA-BEV: Generating Semantic-Aware Bird's-Eye-View Feature for Multi-view 3D Object Detection

PG-RCNN: Semantic Surface Point Generation for 3D Object Detection

5)语义分割

Rethinking Range View Representation for LiDAR Segmentation

Paper:https://arxiv.org/pdf/2303.05367.pdf

UniSeg: A Unified Multi-Modal LiDAR Segmentation Network and the OpenPCSeg Codebase

已收录,arxiv上暂未放出!

Segment Anything

MARS: Model-agnostic Biased Object Removal without Additional Supervision for Weakly-Supervised Semantic Segmentation

Tube-Link: A Flexible Cross Tube Baseline for Universal Video Segmentation

CPCM: Contextual Point Cloud Modeling for Weakly-supervised Point Cloud Semantic Segmentation

To Adapt or Not to Adapt? Real-Time Adaptation for Semantic Segmentation

PointDC: Unsupervised Semantic Segmentation of 3D Point Clouds via Cross-modal Distillation and Super-Voxel Clustering

Contrastive Model Adaptation for Cross-Condition Robustness in Semantic Segmentation

PODA: Prompt-driven Zero-shot Domain Adaptation

Similarity Min-Max: Zero-Shot Day-Night Domain Adaptation

6)点云感知

Robo3D: Towards Robust and Reliable 3D Perception against Corruptions

Implicit Autoencoder for Point Cloud Self-supervised Representation Learning

P2C: Self-Supervised Point Cloud Completion from Single Partial Clouds

CLIP2Point: Transfer CLIP to Point Cloud Classification with Image-Depth Pre-training

SVDFormer: Complementing Point Cloud via Self-view Augmentation and Self-structure Dual-generator

AdaptPoint: Sample-adaptive Augmentation for Point Cloud Recognition Against Real-world Corruptions

RegFormer: An Efficient Projection-Aware Transformer Network for Large-Scale Point Cloud Registration

Point Cloud regression with new algebraical representation on ModelNet40 datasets

Clustering based Point Cloud Representation Learning for 3D Analysis

Implicit Autoencoder for Point Cloud Self-supervised Representation Learning

7)目标跟踪

PVT++: A Simple End-to-End Latency-Aware Visual Tracking Framework

Cross-modal Orthogonal High-rank Augmentation for RGB-Event Transformer-trackers

ReST: A Reconfigurable Spatial-Temporal Graph Model for Multi-Camera Multi-Object Tracking

Multiple Planar Object Tracking

3DMOTFormer: Graph Transformer for Online 3D Multi-Object Tracking

MBPTrack: Improving 3D Point Cloud Tracking with Memory Networks and Box Priors

8) 轨迹预测

EigenTrajectory: Low-Rank Descriptors for Multi-Modal Trajectory Forecasting

9)NeRF

IntrinsicNeRF: Learning Intrinsic Neural Radiance Fields for Editable Novel View Synthesis

SceneRF: Self-Supervised Monocular 3D Scene Reconstruction with Radiance Fields

Single-Stage Diffusion NeRF

10)光流

SemARFlow: Injecting Semantics into Unsupervised Optical Flow Estimation for Autonomous Driving

11)双目

ELFNet: Evidential Local-global Fusion for Stereo Matching

12)鱼眼

SimFIR: A Simple Framework for Fisheye Image Rectification with Self-supervised Representation Learning

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