Papers › FFB6D: A Full Flow Bidirectional Fusion Network for 6D Pose Estimation

FFB6D: A Full Flow Bidirectional Fusion Network for 6D Pose Estimation

3 Mar 2021CVPR 2021 1arXiv:2103.02242archive 2025-07-28

Yisheng He, Haibin Huang, Haoqiang Fan, Qifeng Chen, Jian Sun

In this work, we present FFB6D, a Full Flow Bidirectional fusion network designed for 6D pose estimation from a single RGBD image. Our key insight is that appearance information in the RGB image and geometry information from the depth image are two complementary data sources, and it still remains unknown how to fully leverage them. Towards this end, we propose FFB6D, which learns to combine appearance and geometry information for representation learning as well as output representation selection. Specifically, at the representation learning stage, we build bidirectional fusion modules in the full flow of the two networks, where fusion is applied to each encoding and decoding layer. In this way, the two networks can leverage local and global complementary information from the other one to obtain better representations. Moreover, at the output representation stage, we designed a simple but effective 3D keypoints selection algorithm considering the texture and geometry information of objects, which simplifies keypoint localization for precise pose estimation. Experimental results show that our method outperforms the state-of-the-art by large margins on several benchmarks. Code and video are available at \url{https://github.com/ethnhe/FFB6D.git}.

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ethnhe/FFB6D officialmentioned in papermentioned on GitHubpytorch report
ethnhe/PVN3D mentioned on GitHubpytorch report
hz-ants/FFB6D mentioned on GitHubpytorch report

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DenseFusion ethnhe/PVN3D/pvn3d/lib/pvn3d.py community (archive-listed) ran · metamorphic tier: invariant MIT (permissive) · 957a2ee4964c01ed · report
ModifiedResnet ethnhe/PVN3D/pvn3d/lib/pvn3d.py community (archive-listed) unverified MIT (permissive) · 9a082f752f16d8f1 · report
Modified_PSPNet ethnhe/PVN3D/pvn3d/lib/pvn3d.py community (archive-listed) unverified MIT (permissive) · 81c043aa81be7f81 · report
PVN3D ethnhe/PVN3D/pvn3d/lib/pvn3d.py community (archive-listed) unverified MIT (permissive) · 00f385eabffd4fcf · report
Pointnet2MSG ethnhe/PVN3D/pvn3d/lib/pvn3d.py community (archive-listed) unverified MIT (permissive) · 9d49e2ac7f804eff · report
PointnetFPModule ethnhe/PVN3D/pvn3d/lib/pvn3d.py community (archive-listed) unverified MIT (permissive) · 2ce442ec443b4c7d · report
PointnetSAModuleMSG ethnhe/PVN3D/pvn3d/lib/pvn3d.py community (archive-listed) unverified MIT (permissive) · 86a12407c21929a5 · report
_PointnetSAModuleBase ethnhe/PVN3D/pvn3d/lib/pvn3d.py community (archive-listed) unverified MIT (permissive) · 01b40719ce9b7148 · report

Tasks

6D Pose EstimationPose EstimationRepresentation Learning

Results from the paper archive 2025-07-28

TaskDatasetModelMetricValueRank at snapshotLeaderboardReport
6D Pose Estimation LineMOD FFB6D Accuracy (ADD) 99.7 #1 of 5 Archive leaderboard report
6D Pose Estimation YCB-Video FFB6D ADDS AUC 96.6 #2 of 10 Archive leaderboard report

Ranks are positions in the archive's leaderboards as they stood at the 2025-07-28 snapshot. Results published since then are not among these rows, so a rank here is not a current standing.

Methods

Introduced by this paper: FFB6D

FFB6D

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