2D Object Detection
84 papers with code • 14 benchmarks • 57 datasets
Benchmarks
These leaderboards are used to track progress in 2D Object Detection
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Libraries
Use these libraries to find 2D Object Detection models and implementationsDatasets
BDD100K
VisDrone
Hypersim
COCO-O
ExDark
Clear Weather
KITTI MOTS
FlickrLogos-32
RADIATE
PACO
Subtasks
Latest papers with no code
Informative Data Selection with Uncertainty for Multi-modal Object Detection
To quantify the correlation in multi-modal information, we model the uncertainty, as the inverse of data information, in different modalities and embed it in the bounding box generation.
EvCenterNet: Uncertainty Estimation for Object Detection using Evidential Learning
In this work, we propose EvCenterNet, a novel uncertainty-aware 2D object detection framework using evidential learning to directly estimate both classification and regression uncertainties.
TRR360D: A dataset for 360 degree rotated rectangular box table detection
To address the problem of scarcity and high annotation costs of rotated image table detection datasets, this paper proposes a method for building a rotated image table detection dataset.
BOP Challenge 2022 on Detection, Segmentation and Pose Estimation of Specific Rigid Objects
In 2022, we witnessed another significant improvement in the pose estimation accuracy -- the state of the art, which was 56. 9 AR$_C$ in 2019 (Vidal et al.) and 69. 8 AR$_C$ in 2020 (CosyPose), moved to new heights of 83. 7 AR$_C$ (GDRNPP).
Model-Based Underwater 6D Pose Estimation from RGB
All objects and scenes are made available in an open-source dataset that includes annotations for object detection and pose estimation.
Bridging the Sim2Real gap with CARE: Supervised Detection Adaptation with Conditional Alignment and Reweighting
Sim2Real domain adaptation (DA) research focuses on the constrained setting of adapting from a labeled synthetic source domain to an unlabeled or sparsely labeled real target domain.
DR-WLC: Dimensionality Reduction cognition for object detection and pose estimation by Watching, Learning and Checking
For example, 2D object detection usually requires a large amount of 2D annotation data with high cost.
Poses of People in Art: A Data Set for Human Pose Estimation in Digital Art History
With the Poses of People in Art data set, we introduce the first openly licensed data set for estimating human poses in art and validating human pose estimators.
Monocular 3D Object Detection using Multi-Stage Approaches with Attention and Slicing aided hyper inference
3D object detection is vital as it would enable us to capture objects' sizes, orientation, and position in the world.
Objects as Spatio-Temporal 2.5D points
Determining accurate bird's eye view (BEV) positions of objects and tracks in a scene is vital for various perception tasks including object interactions mapping, scenario extraction etc., however, the level of supervision required to accomplish that is extremely challenging to procure.
