Delving into the devils of bird's-eye-view perception: A review, evaluation and recipe
Learning powerful representations in bird's-eye-view (BEV) for perception tasks is trending
and drawing extensive attention both from industry and academia. Conventional …
and drawing extensive attention both from industry and academia. Conventional …
3D object detection for autonomous driving: A comprehensive survey
Autonomous driving, in recent years, has been receiving increasing attention for its potential
to relieve drivers' burdens and improve the safety of driving. In modern autonomous driving …
to relieve drivers' burdens and improve the safety of driving. In modern autonomous driving …
Depth anything: Unleashing the power of large-scale unlabeled data
Abstract This work presents Depth Anything a highly practical solution for robust monocular
depth estimation. Without pursuing novel technical modules we aim to build a simple yet …
depth estimation. Without pursuing novel technical modules we aim to build a simple yet …
Bevdepth: 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 …
dubbed BEVDepth, for camera-based Bird's-Eye-View~(BEV) 3D object detection. Our work …
Unifying voxel-based representation with transformer for 3d object detection
In this work, we present a unified framework for multi-modality 3D object detection, named
UVTR. The proposed method aims to unify multi-modality representations in the voxel space …
UVTR. The proposed method aims to unify multi-modality representations in the voxel space …
Bytetrack: Multi-object tracking by associating every detection box
Multi-object tracking (MOT) aims at estimating bounding boxes and identities of objects in
videos. Most methods obtain identities by associating detection boxes whose scores are …
videos. Most methods obtain identities by associating detection boxes whose scores are …
Transfuser: Imitation with transformer-based sensor fusion for autonomous driving
How should we integrate representations from complementary sensors for autonomous
driving? Geometry-based fusion has shown promise for perception (eg, object detection …
driving? Geometry-based fusion has shown promise for perception (eg, object detection …
Logonet: Towards accurate 3d object detection with local-to-global cross-modal fusion
LiDAR-camera fusion methods have shown impressive performance in 3D object detection.
Recent advanced multi-modal methods mainly perform global fusion, where image features …
Recent advanced multi-modal methods mainly perform global fusion, where image features …
Fcos3d: Fully convolutional one-stage monocular 3d object detection
Monocular 3D object detection is an important task for autonomous driving considering its
advantage of low cost. It is much more challenging than conventional 2D cases due to its …
advantage of low cost. It is much more challenging than conventional 2D cases due to its …
Is pseudo-lidar needed for monocular 3d object detection?
Recent progress in 3D object detection from single images leverages monocular depth
estimation as a way to produce 3D pointclouds, turning cameras into pseudo-lidar sensors …
estimation as a way to produce 3D pointclouds, turning cameras into pseudo-lidar sensors …