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Found 10 papers, 7 papers with code
Diffusion Models with Deterministic Normalizing Flow Priors
We use normalizing flows to parameterize the noisy data at any arbitrary step of the diffusion process and utilize it as the prior in the reverse diffusion process.
Multiscale Residual Learning of Graph Convolutional Sequence Chunks for Human Motion Prediction
Our experiments on two challenging benchmark datasets, CMU Mocap and Human3. 6M, demonstrate that our proposed method is able to effectively model the sequence information for motion prediction and outperform other techniques to set a new state-of-the-art.
Diffusion Dataset Generation: Towards Closing the Sim2Real Gap for Pedestrian Detection
We propose a method that augments a simulated dataset using diffusion models to improve the performance of pedestrian detection in real-world data.
Keypoint Cascade Voting for Point Cloud Based 6DoF Pose Estimation
We propose a novel keypoint voting 6DoF object pose estimation method, which takes pure unordered point cloud geometry as input without RGB information.
ObjectBox: From Centers to Boxes for Anchor-Free Object Detection
We present ObjectBox, a novel single-stage anchor-free and highly generalizable object detection approach.
Multiscale Crowd Counting and Localization By Multitask Point Supervision
As the detection and localization tasks are well-correlated and can be jointly tackled, our model benefits from a multitask solution by learning multiscale representations of encoded crowd images, and subsequently fusing them.
Multistream ValidNet: Improving 6D Object Pose Estimation by Automatic Multistream Validation
Applying our method can also improve the pose estimation average precision results of Op-Net by 6. 06% on average.
Oriented Bounding Boxes for Small and Freely Rotated Objects
A novel object detection method is presented that handles freely rotated objects of arbitrary sizes, including tiny objects as small as $2\times 2$ pixels.
Flow-based Spatio-Temporal Structured Prediction of Motion Dynamics
We specifically propose to use conditional priors to factorize the latent space for the time dependent modeling.
Vote from the Center: 6 DoF Pose Estimation in RGB-D Images by Radial Keypoint Voting
We propose a novel keypoint voting scheme based on intersecting spheres, that is more accurate than existing schemes and allows for fewer, more disperse keypoints.
Ranked #1 on
6D Pose Estimation using RGBD
on YCB-Video
(ADDS AUC metric)
