Viewpoints and Keypoints
We characterize the problem of pose estimation for rigid objects in terms of determining viewpoint to explain coarse pose and keypoint prediction to capture the finer details. We address both these tasks in two different settings - the constrained setting with known bounding boxes and the more challenging detection setting where the aim is to simultaneously detect and correctly estimate pose of objects. We present Convolutional Neural Network based architectures for these and demonstrate that leveraging viewpoint estimates can substantially improve local appearance based keypoint predictions. In addition to achieving significant improvements over state-of-the-art in the above tasks, we analyze the error modes and effect of object characteristics on performance to guide future efforts towards this goal.
Code (0)
등록된 구현이 없습니다.
Tasks
Keypoint DetectionPose EstimationSimilar Papers 제목 키워드 기반
Weakly Supervised Learning of Keypoints for 6D Object Pose Estimation
State-of-the-art approaches for 6D object pose estimation require large amounts of labeled data to train the deep networks. However, the acquisition of 6D object pose annotations is tedious and labor-intensive in large q…
6D Pose Estimation using RGBKeypoint DetectionObjectPose Estimation+1Joint Viewpoint and Keypoint Estimation with Real and Synthetic Data
The estimation of viewpoints and keypoints effectively enhance object detection methods by extracting valuable traits of the object instances. While the output of both processes differ, i.e., angles vs. list of character…
Keypoint EstimationObjectobject-detectionObject DetectionWeakly Supervised Keypoint Discovery
In this paper, we propose a method for keypoint discovery from a 2D image using image-level supervision. Recent works on unsupervised keypoint discovery reliably discover keypoints of aligned instances. However, when the…
Conditional Image GenerationImage GenerationKeypoint EstimationWeakly-supervised LearningLearning Deep Network for Detecting 3D Object Keypoints and 6D Poses
The state-of-art 6D object pose detection methods use convolutional neural networks to estimate objects' 6D poses from RGB images. However, they require huge numbers of images with explicit 3D annotations such as 6D pose…
ObjectPose EstimationFoundHand: Large-Scale Domain-Specific Learning for Controllable Hand Image Generation
Despite remarkable progress in image generation models, generating realistic hands remains a persistent challenge due to their complex articulation, varying viewpoints, and frequent occlusions. We present FoundHand, a la…
Image Generation