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Found 10 papers, 4 papers with code
Semantic-Rearrangement-Based Multi-Level Alignment for Domain Generalized Segmentation
SRMA first incorporates a Semantic Rearrangement Module (SRM), which conducts semantic region randomization to enhance the diversity of the source domain sufficiently.
RaSim: A Range-aware High-fidelity RGB-D Data Simulation Pipeline for Real-world Applications
In robotic vision, a de-facto paradigm is to learn in simulated environments and then transfer to real-world applications, which poses an essential challenge in bridging the sim-to-real domain gap.
KP-RED: Exploiting Semantic Keypoints for Joint 3D Shape Retrieval and Deformation
In this paper, we present KP-RED, a unified KeyPoint-driven REtrieval and Deformation framework that takes object scans as input and jointly retrieves and deforms the most geometrically similar CAD models from a pre-processed database to tightly match the target.
D-SCo: Dual-Stream Conditional Diffusion for Monocular Hand-Held Object Reconstruction
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.
SecondPose: SE(3)-Consistent Dual-Stream Feature Fusion for Category-Level Pose Estimation
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.
MOHO: Learning Single-view Hand-held Object Reconstruction with Multi-view Occlusion-Aware Supervision
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.
CCD-3DR: Consistent Conditioning in Diffusion for Single-Image 3D Reconstruction
However, such strategies fail to consistently align the denoised point cloud with the given image, leading to unstable conditioning and inferior performance.
U-RED: Unsupervised 3D Shape Retrieval and Deformation for Partial Point Clouds
In this paper, we propose U-RED, an Unsupervised shape REtrieval and Deformation pipeline that takes an arbitrary object observation as input, typically captured by RGB images or scans, and jointly retrieves and deforms the geometrically similar CAD models from a pre-established database to tightly match the target.
SST: Real-time End-to-end Monocular 3D Reconstruction via Sparse Spatial-Temporal Guidance
Real-time monocular 3D reconstruction is a challenging problem that remains unsolved.
