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Monocular 3D Object Detection

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평가표: 16
보존된 평가 기록: 72

Monocular 3D Object Detection is the task to draw 3D bounding box around objects in a single 2D RGB image. It is localization task but without any extra information like depth or other sensors or multiple-images.

논문

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SpikeSMOKE: Spiking Neural Networks for Monocular 3D Object Detection with Cross-Scale Gated Coding

MonoCoP: Chain-of-Prediction for Monocular 3D Object Detection

Weak Cube R-CNN: Weakly Supervised 3D Detection using only 2D Bounding Boxes

GATE3D: Generalized Attention-based Task-synergized Estimation in 3D*

MonoCT: Overcoming Monocular 3D Detection Domain Shift with Consistent Teacher Models

IROAM: Improving Roadside Monocular 3D Object Detection Learning from Autonomous Vehicle Data Domain

AuxDepthNet: Real-Time Monocular 3D Object Detection with Depth-Sensitive Features

Revisiting Monocular 3D Object Detection from Scene-Level Depth Retargeting to Instance-Level Spatial Refinement

V-MIND: Building Versatile Monocular Indoor 3D Detector with Diverse 2D Annotations

Open Vocabulary Monocular 3D Object Detection

Training an Open-Vocabulary Monocular 3D Object Detection Model without 3D Data

Efficient Feature Aggregation and Scale-Aware Regression for Monocular 3D Object Detection

MonoDGP: Monocular 3D Object Detection with Decoupled-Query and Geometry-Error Priors

HeightFormer: A Semantic Alignment Monocular 3D Object Detection Method from Roadside Perspective

Transfer Learning from Simulated to Real Scenes for Monocular 3D Object Detection

CARLA Drone: Monocular 3D Object Detection from a Different Perspective

LAM3D: Leveraging Attention for Monocular 3D Object Detection

MonoMM: A Multi-scale Mamba-Enhanced Network for Real-time Monocular 3D Object Detection

WARM-3D: A Weakly-Supervised Sim2Real Domain Adaptation Framework for Roadside Monocular 3D Object Detection

MonoWAD: Weather-Adaptive Diffusion Model for Robust Monocular 3D Object Detection

LabelDistill: Label-guided Cross-modal Knowledge Distillation for Camera-based 3D Object Detection

Fully Test-Time Adaptation for Monocular 3D Object Detection

MonoDETRNext: Next-Generation Accurate and Efficient Monocular 3D Object Detector

MonoMAE: Enhancing Monocular 3D Detection through Depth-Aware Masked Autoencoders

VFMM3D: Releasing the Potential of Image by Vision Foundation Model for Monocular 3D Object Detection

MOSE: Boosting Vision-based Roadside 3D Object Detection with Scene Cues

MonoTAKD: Teaching Assistant Knowledge Distillation for Monocular 3D Object Detection

MonoCD: Monocular 3D Object Detection with Complementary Depths

VSRD: Instance-Aware Volumetric Silhouette Rendering for Weakly Supervised 3D Object Detection

Decoupled Pseudo-labeling for Semi-Supervised Monocular 3D Object Detection

Multi-task Learning for Real-time Autonomous Driving Leveraging Task-adaptive Attention Generator

Towards Unified 3D Object Detection via Algorithm and Data Unification

You Only Look Bottom-Up for Monocular 3D Object Detection

Depth-discriminative Metric Learning for Monocular 3D Object Detection

MonoLSS: Learnable Sample Selection For Monocular 3D Detection

Mono3DVG: 3D Visual Grounding in Monocular Images

출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.