# SecondPose: SE(3)-Consistent Dual-Stream Feature Fusion for Category-Level Pose Estimation

arXiv: https://arxiv.org/abs/2311.11125 · HTML: https://mlsanity.com/paper/2311.11125/

## Key facts

- Cited by 53 papers in the map (data through 14 Oct 2026).
- Builds on 47 of its 58 references that are in the map.
- First posted on arXiv 18 Nov 2023.

## Builds on (most cited first, 30 of 47)

- [Mask R-CNN](https://mlsanity.com/paper/1703.06870/) (2017)
- [PointNet++: Deep Hierarchical Feature Learning on Point Sets in a Metric Space](https://mlsanity.com/paper/1706.02413/) (2017)
- [PoseCNN: A Convolutional Neural Network for 6D Object Pose Estimation in Cluttered Scenes](https://mlsanity.com/paper/1711.00199/) (2017)
- [Normalized Object Coordinate Space for Category-Level 6D Object Pose and Size Estimation](https://mlsanity.com/paper/1901.02970/) (2019)
- [PVNet: Pixel-wise Voting Network for 6DoF Pose Estimation](https://mlsanity.com/paper/1812.11788/) (2018)
- [DenseFusion: 6D Object Pose Estimation by Iterative Dense Fusion](https://mlsanity.com/paper/1901.04780/) (2019)
- [A Tale of Two Features: Stable Diffusion Complements DINO for Zero-Shot Semantic Correspondence](https://mlsanity.com/paper/2305.15347/) (2023)
- [CosyPose: Consistent multi-view multi-object 6D pose estimation](https://mlsanity.com/paper/2008.08465/) (2020)
- [SSD-6D: Making RGB-based 3D detection and 6D pose estimation great again](https://mlsanity.com/paper/1711.10006/) (2017)
- [PVN3D: A Deep Point-wise 3D Keypoints Voting Network for 6DoF Pose Estimation](https://mlsanity.com/paper/1911.04231/) (2019)
- [DPOD: 6D Pose Object Detector and Refiner](https://mlsanity.com/paper/1902.11020/) (2019)
- [Implicit 3D Orientation Learning for 6D Object Detection from RGB Images](https://mlsanity.com/paper/1902.01275/) (2019)
- [Shape Prior Deformation for Categorical 6D Object Pose and Size Estimation](https://mlsanity.com/paper/2007.08454/) (2020)
- [GDRNPP: A Geometry-guided and Fully Learning-based Object Pose Estimator](https://mlsanity.com/paper/2102.12145/) (2021)
- [FFB6D: A Full Flow Bidirectional Fusion Network for 6D Pose Estimation](https://mlsanity.com/paper/2103.02242/) (2021)
- [Learning Canonical Shape Space for Category-Level 6D Object Pose and Size Estimation](https://mlsanity.com/paper/2001.09322/) (2020)
- [FS-Net: Fast Shape-based Network for Category-Level 6D Object Pose Estimation with Decoupled Rotation Mechanism](https://mlsanity.com/paper/2103.07054/) (2021)
- [ZebraPose: Coarse to Fine Surface Encoding for 6DoF Object Pose Estimation](https://mlsanity.com/paper/2203.09418/) (2022)
- [DualPoseNet: Category-level 6D Object Pose and Size Estimation Using Dual Pose Network with Refined Learning of Pose Consistency](https://mlsanity.com/paper/2103.06526/) (2021)
- [GPV-Pose: Category-level Object Pose Estimation via Geometry-guided Point-wise Voting](https://mlsanity.com/paper/2203.07918/) (2022)
- [SO-Pose: Exploiting Self-Occlusion for Direct 6D Pose Estimation](https://mlsanity.com/paper/2108.08367/) (2021)
- [CNOS: A Strong Baseline for CAD-based Novel Object Segmentation](https://mlsanity.com/paper/2307.11067/) (2023)
- [CAPTRA: CAtegory-level Pose Tracking for Rigid and Articulated Objects from Point Clouds](https://mlsanity.com/paper/2104.03437/) (2021)
- [Category-Level 6D Object Pose and Size Estimation using Self-Supervised Deep Prior Deformation Networks](https://mlsanity.com/paper/2207.05444/) (2022)
- [CenterSnap: Single-Shot Multi-Object 3D Shape Reconstruction and Categorical 6D Pose and Size Estimation](https://mlsanity.com/paper/2203.01929/) (2022)
- [Category-Level 6D Object Pose Estimation via Cascaded Relation and Recurrent Reconstruction Networks](https://mlsanity.com/paper/2108.08755/) (2021)
- [Zero-Shot Category-Level Object Pose Estimation](https://mlsanity.com/paper/2204.03635/) (2022)
- [SAR-Net: Shape Alignment and Recovery Network for Category-level 6D Object Pose and Size Estimation](https://mlsanity.com/paper/2106.14193/) (2021)
- [HS-Pose: Hybrid Scope Feature Extraction for Category-level Object Pose Estimation](https://mlsanity.com/paper/2303.15743/) (2023)
- [RBP-Pose: Residual Bounding Box Projection for Category-Level Pose Estimation](https://mlsanity.com/paper/2208.00237/) (2022)

## Built on by (most cited first, 30 of 53)

- [Scenethesis: A Language and Vision Agentic Framework for 3D Scene Generation](https://mlsanity.com/paper/2505.02836/) (2025)
- [Any6D: Model-free 6D Pose Estimation of Novel Objects](https://mlsanity.com/paper/2503.18673/) (2025)
- [Deep Learning-Based Object Pose Estimation: A Comprehensive Survey](https://mlsanity.com/paper/2405.07801/) (2024)
- [GCE-Pose: Global Context Enhancement for Category-level Object Pose Estimation](https://mlsanity.com/paper/2502.04293/) (2025)
- [Diff9D: Diffusion-Based Domain-Generalized Category-Level 9-DoF Object Pose Estimation](https://mlsanity.com/paper/2502.02525/) (2025)
- [LaPose: Laplacian Mixture Shape Modeling for RGB-Based Category-Level Object Pose Estimation](https://mlsanity.com/paper/2409.15727/) (2024)
- [UNOPose: Unseen Object Pose Estimation with an Unposed RGB-D Reference Image](https://mlsanity.com/paper/2411.16106/) (2024)
- [Zero123-6D: Zero-shot Novel View Synthesis for RGB Category-level 6D Pose Estimation](https://mlsanity.com/paper/2403.14279/) (2024)
- [CleanPose: Category-Level Object Pose Estimation via Causal Learning and Knowledge Distillation](https://mlsanity.com/paper/2502.01312/) (2025)
- [Learning Shape-Independent Transformation via Spherical Representations for Category-Level Object Pose Estimation](https://mlsanity.com/paper/2503.13926/) (2025)
- [GIVEPose: Gradual Intra-class Variation Elimination for RGB-based Category-Level Object Pose Estimation](https://mlsanity.com/paper/2503.15110/) (2025)
- [Foundation Visual Encoders Are Secretly Few-Shot Anomaly Detectors](https://mlsanity.com/paper/2510.01934/) (2025)
- [Diffusion Features for Zero-Shot 6DoF Object Pose Estimation](https://mlsanity.com/paper/2411.16668/) (2024)
- [Unified Category-Level Object Detection and Pose Estimation from RGB Images using 3D Prototypes](https://mlsanity.com/paper/2508.02157/) (2025)
- [RayPose: Ray Bundling Diffusion for Template Views in Unseen 6D Object Pose Estimation](https://mlsanity.com/paper/2510.18521/) (2025)
- [ComPose: A Unified Completion-Pose Framework for Robust Category-Level Object Pose Estimation](https://mlsanity.com/paper/2605.25553/) (2026)
- [Structure-Aware Correspondence Learning for Relative Pose Estimation](https://mlsanity.com/paper/2503.18671/) (2025)
- [BoxDreamer: Dreaming Box Corners for Generalizable Object Pose Estimation](https://mlsanity.com/paper/2504.07955/) (2025)
- [Forecasting Continuous Non-Conservative Dynamical Systems in SO(3)](https://mlsanity.com/paper/2508.07775/) (2025)
- [Category-Level Object Shape and Pose Estimation in Less Than a Millisecond](https://mlsanity.com/paper/2509.18979/) (2025)
- [UnPose: Uncertainty-Guided Diffusion Priors for Zero-Shot Pose Estimation](https://mlsanity.com/paper/2508.15972/) (2025)
- [fCOP: Focal Length Estimation from Category-level Object Priors](https://mlsanity.com/paper/2409.19641/) (2024)
- [Object Pose Estimation Using Implicit Representation For Transparent Objects](https://mlsanity.com/paper/2410.13465/) (2024)
- [Instance-Adaptive Keypoint Learning with Local-to-Global Geometric Aggregation for Category-Level Object Pose Estimation](https://mlsanity.com/paper/2504.15134/) (2025)
- [Joint Learning of Pose Regression and Denoising Diffusion with Score Scaling Sampling for Category-level 6D Pose Estimation](https://mlsanity.com/paper/2510.04125/) (2025)
- [OPFormer: Object Pose Estimation leveraging foundation model with geometric encoding](https://mlsanity.com/paper/2511.12614/) (2025)
- [CanoVerse: 3D Object Scalable Canonicalization and Dataset for Generation and Pose](https://mlsanity.com/paper/2603.07144/) (2026)
- [OCH3R: Object-Centric Holistic 3D Reconstruction](https://mlsanity.com/paper/2605.13018/) (2026)
- [Flow6D: Discrete-to-Continuous Flow Matching for Efficient and Accurate Category-Level 6D Pose Estimation](https://mlsanity.com/paper/2606.23293/) (2026)
- [MemPose: Category-level Object Pose Estimation with Memory](https://mlsanity.com/paper/2607.04930/) (2026)

## Abstract (arXiv)

Category-level object pose estimation, aiming to predict the 6D pose and 3D size of objects from known categories, typically struggles with large intra-class shape variation. Existing works utilizing mean shapes often fall short of capturing this variation. To address this issue, we present SecondPose, a novel approach integrating object-specific geometric features with semantic category priors from DINOv2. Leveraging the advantage of DINOv2 in providing SE(3)-consistent semantic features, we hierarchically extract two types of SE(3)-invariant geometric features to further encapsulate local-to-global object-specific information. These geometric features are then point-aligned with DINOv2 features to establish a consistent object representation under SE(3) transformations, facilitating the mapping from camera space to the pre-defined canonical space, thus further enhancing pose estimation. Extensive experiments on NOCS-REAL275 demonstrate that SecondPose achieves a 12.4% leap forward over the state-of-the-art. Moreover, on a more complex dataset HouseCat6D which provides photometrically challenging objects, SecondPose still surpasses other competitors by a large margin.