Papers Robust Camera Only 3D Object Detection
“Robust Camera Only 3D Object Detection” 태그가 달린 논문 12편 · 필터 해제
RoboBEV: Towards Robust Bird's Eye View Perception under Corruptions
The recent advances in camera-based bird's eye view (BEV) representation exhibit great potential for in-vehicle 3D perception. Despite the substantial progress achieved on standard benchmarks, the robustness of BEV algor…
Robust Camera Only 3D Object DetectionSparse4D: Multi-view 3D Object Detection with Sparse Spatial-Temporal Fusion
Bird-eye-view (BEV) based methods have made great progress recently in multi-view 3D detection task. Comparing with BEV based methods, sparse based methods lag behind in performance, but still have lots of non-negligible…
3D Object Detectionobject-detectionObject DetectionRobust Camera Only 3D Object DetectionTime Will Tell: New Outlooks and A Baseline for Temporal Multi-View 3D Object Detection
While recent camera-only 3D detection methods leverage multiple timesteps, the limited history they use significantly hampers the extent to which temporal fusion can improve object perception. Observing that existing wor…
3D Object Detectionobject-detectionObject DetectionRobust Camera Only 3D Object Detection+1ORA3D: Overlap Region Aware Multi-view 3D Object Detection
Current multi-view 3D object detection methods often fail to detect objects in the overlap region properly, and the networks' understanding of the scene is often limited to that of a monocular detection network. Moreover…
3D Object DetectionDisparity EstimationObjectobject-detection+3PolarFormer: Multi-camera 3D Object Detection with Polar Transformer
3D object detection in autonomous driving aims to reason "what" and "where" the objects of interest present in a 3D world. Following the conventional wisdom of previous 2D object detection, existing methods often adopt t…
2D Object Detection3D Object DetectionAutonomous DrivingObject+5SRCN3D: Sparse R-CNN 3D for Compact Convolutional Multi-View 3D Object Detection and Tracking
Detection and tracking of moving objects is an essential component in environmental perception for autonomous driving. In the flourishing field of multi-view 3D camera-based detectors, different transformer-based pipelin…
3D Multi-Object Tracking3D Object DetectionAutonomous DrivingMulti-Object Tracking+5BEVDepth: Acquisition of Reliable Depth for Multi-view 3D Object Detection
In this research, we propose a new 3D object detector with a trustworthy depth estimation, dubbed BEVDepth, for camera-based Bird's-Eye-View (BEV) 3D object detection. Our work is based on a key observation -- depth esti…
3D Object DetectionDepth EstimationObject DetectionRobust Camera Only 3D Object DetectionBEVerse: Unified Perception and Prediction in Birds-Eye-View for Vision-Centric Autonomous Driving
In this paper, we present BEVerse, a unified framework for 3D perception and prediction based on multi-camera systems. Unlike existing studies focusing on the improvement of single-task approaches, BEVerse features in pr…
3D Object DetectionAutonomous DrivingFuture predictionmotion prediction+4BEVFormer: Learning Bird's-Eye-View Representation from Multi-Camera Images via Spatiotemporal Transformers
3D visual perception tasks, including 3D detection and map segmentation based on multi-camera images, are essential for autonomous driving systems. In this work, we present a new framework termed BEVFormer, which learns …
3D Object DetectionAutonomous DrivingBird's-Eye View Semantic SegmentationRobust Camera Only 3D Object DetectionPETR: Position Embedding Transformation for Multi-View 3D Object Detection
In this paper, we develop position embedding transformation (PETR) for multi-view 3D object detection. PETR encodes the position information of 3D coordinates into image features, producing the 3D position-aware features…
3D Object DetectionObjectobject-detectionObject Detection+2BEVDet: High-performance Multi-camera 3D Object Detection in Bird-Eye-View
Autonomous driving perceives its surroundings for decision making, which is one of the most complex scenarios in visual perception. The success of paradigm innovation in solving the 2D object detection task inspires us t…
3D Object DetectionAutonomous DrivingData Augmentationobject-detection+2DETR3D: 3D Object Detection from Multi-view Images via 3D-to-2D Queries
We introduce a framework for multi-camera 3D object detection. In contrast to existing works, which estimate 3D bounding boxes directly from monocular images or use depth prediction networks to generate input for 3D obje…
3D Object DetectionAutonomous DrivingDepth EstimationDepth Prediction+5