Search Results for author: Gu Wang

Found 13 papers, 6 papers with code

D-SCo: Dual-Stream Conditional Diffusion for Monocular Hand-Held Object Reconstruction

no code implementations23 Nov 2023 Bowen Fu, Gu Wang, Chenyangguang Zhang, Yan Di, Ziqin Huang, Zhiying Leng, Fabian Manhardt, Xiangyang Ji, Federico Tombari

Second, we introduce a dual-stream denoiser to semantically and geometrically model hand-object interactions with a novel unified hand-object semantic embedding, enhancing the reconstruction performance of the hand-occluded region of the object.

Denoising Object +1

MOHO: Learning Single-view Hand-held Object Reconstruction with Multi-view Occlusion-Aware Supervision

no code implementations18 Oct 2023 Chenyangguang Zhang, Guanlong Jiao, Yan Di, Gu Wang, Ziqin Huang, Ruida Zhang, Fabian Manhardt, Bowen Fu, Federico Tombari, Xiangyang Ji

Previous works concerning single-view hand-held object reconstruction typically rely on supervision from 3D ground-truth models, which are hard to collect in real world.

Object Object Reconstruction

BOP Challenge 2022 on Detection, Segmentation and Pose Estimation of Specific Rigid Objects

no code implementations25 Feb 2023 Martin Sundermeyer, Tomas Hodan, Yann Labbe, Gu Wang, Eric Brachmann, Bertram Drost, Carsten Rother, Jiri Matas

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).

6D Pose Estimation using RGB object-detection +1

CATRE: Iterative Point Clouds Alignment for Category-level Object Pose Refinement

1 code implementation17 Jul 2022 Xingyu Liu, Gu Wang, Yi Li, Xiangyang Ji

While category-level 9DoF object pose estimation has emerged recently, previous correspondence-based or direct regression methods are both limited in accuracy due to the huge intra-category variances in object shape and color, etc.

Object Pose Estimation

SO-Pose: Exploiting Self-Occlusion for Direct 6D Pose Estimation

2 code implementations ICCV 2021 Yan Di, Fabian Manhardt, Gu Wang, Xiangyang Ji, Nassir Navab, Federico Tombari

Directly regressing all 6 degrees-of-freedom (6DoF) for the object pose (e. g. the 3D rotation and translation) in a cluttered environment from a single RGB image is a challenging problem.

6D Pose Estimation 6D Pose Estimation using RGB +1

GDR-Net: Geometry-Guided Direct Regression Network for Monocular 6D Object Pose Estimation

1 code implementation CVPR 2021 Gu Wang, Fabian Manhardt, Federico Tombari, Xiangyang Ji

In this work, we perform an in-depth investigation on both direct and indirect methods, and propose a simple yet effective Geometry-guided Direct Regression Network (GDR-Net) to learn the 6D pose in an end-to-end manner from dense correspondence-based intermediate geometric representations.

6D Pose Estimation 6D Pose Estimation using RGB +1

DeepIM: Deep Iterative Matching for 6D Pose Estimation

2 code implementations ECCV 2018 Yi Li, Gu Wang, Xiangyang Ji, Yu Xiang, Dieter Fox

Estimating the 6D pose of objects from images is an important problem in various applications such as robot manipulation and virtual reality.

6D Pose Estimation 6D Pose Estimation using RGB +1

Action Recognition with Joint Attention on Multi-Level Deep Features

no code implementations9 Jul 2016 Jialin Wu, Gu Wang, Wukui Yang, Xiangyang Ji

We propose a novel deep supervised neural network for the task of action recognition in videos, which implicitly takes advantage of visual tracking and shares the robustness of both deep Convolutional Neural Network (CNN) and Recurrent Neural Network (RNN).

Action Recognition In Videos Temporal Action Localization +1

Cannot find the paper you are looking for? You can Submit a new open access paper.