HyperAI
HyperAI
Startseite
Plattform
Dokumentation
Neuigkeiten
Forschungsarbeiten
Tutorials
Datensätze
Wiki
SOTA
LLM-Modelle
GPU-Rangliste
Veranstaltungen
Suche
Über
Nutzungsbedingungen
Datenschutzrichtlinie
Deutsch
HyperAI
HyperAI
Toggle Sidebar
Seite durchsuchen…
⌘
K
Command Palette
Search for a command to run...
Plattform
Startseite
SOTA
6D-Pose-Schätzung mittels RGBD
6D Pose Estimation Using Rgbd On Ycb Video
6D Pose Estimation Using Rgbd On Ycb Video
Metriken
Mean ADD
Ergebnisse
Leistungsergebnisse verschiedener Modelle zu diesem Benchmark
Columns
Modellname
Mean ADD
Paper Title
CMCL6D
95.43
Enhancing 6-DoF Object Pose Estimation through Multiple Modality Fusion: A Hybrid CNN Architecture with Cross-Layer and Cross-Modal Integration
MaskedFusion
93.3
MaskedFusion: Mask-based 6D Object Pose Estimation
PoseCNN + DeepIM
80.6
DeepIM: Deep Iterative Matching for 6D Pose Estimation
PoseCNN (ICP)
79.3
PoseCNN: A Convolutional Neural Network for 6D Object Pose Estimation in Cluttered Scenes
RCVPose
-
Vote from the Center: 6 DoF Pose Estimation in RGB-D Images by Radial Keypoint Voting
PVN3D
-
PVN3D: A Deep Point-wise 3D Keypoints Voting Network for 6DoF Pose Estimation
RCVPose+ICP
-
Vote from the Center: 6 DoF Pose Estimation in RGB-D Images by Radial Keypoint Voting
ALL PoseCNN+ICP
-
PoseCNN: A Convolutional Neural Network for 6D Object Pose Estimation in Cluttered Scenes
0 of 8 row(s) selected.
Previous
Next
6D Pose Estimation Using Rgbd On Ycb Video | SOTA | HyperAI