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Found 13 papers, 8 papers with code
Generic 3D Diffusion Adapter Using Controlled Multi-View Editing
Open-domain 3D object synthesis has been lagging behind image synthesis due to limited data and higher computational complexity.
Towards Learning Geometric Eigen-Lengths Crucial for Fitting Tasks
In this work, we therefore for the first time formulate and propose a novel learning problem on this question and set up a benchmark suite including tasks, data, and evaluation metrics for studying the problem.
PACE: A Large-Scale Dataset with Pose Annotations in Cluttered Environments
We introduce PACE (Pose Annotations in Cluttered Environments), a large-scale benchmark designed to advance the development and evaluation of pose estimation methods in cluttered scenarios.
ZeroRF: Fast Sparse View 360° Reconstruction with Zero Pretraining
We present ZeroRF, a novel per-scene optimization method addressing the challenge of sparse view 360{\deg} reconstruction in neural field representations.
One-2-3-45++: Fast Single Image to 3D Objects with Consistent Multi-View Generation and 3D Diffusion
Recent advancements in open-world 3D object generation have been remarkable, with image-to-3D methods offering superior fine-grained control over their text-to-3D counterparts.
Zero123++: a Single Image to Consistent Multi-view Diffusion Base Model
We report Zero123++, an image-conditioned diffusion model for generating 3D-consistent multi-view images from a single input view.
OpenShape: Scaling Up 3D Shape Representation Towards Open-World Understanding
Due to their alignment with CLIP embeddings, our learned shape representations can also be integrated with off-the-shelf CLIP-based models for various applications, such as point cloud captioning and point cloud-conditioned image generation.
Ranked #5 on
Zero-Shot Transfer 3D Point Cloud Classification
on ModelNet40
(using extra training data)
RendNet: Unified 2D/3D Recognizer With Latent Space Rendering
Instead of looking at one format, it is a good solution to utilize the formats of VG and RG together to avoid these shortcomings.
CPPF: Towards Robust Category-Level 9D Pose Estimation in the Wild
Drawing inspirations from traditional point pair features (PPFs), in this paper, we design a novel Category-level PPF (CPPF) voting method to achieve accurate, robust and generalizable 9D pose estimation in the wild.
Ranked #8 on
6D Pose Estimation using RGBD
on REAL275
Energy Attack: On Transferring Adversarial Examples
Base on the eigenvalues, we can model the energy distribution of adversarial perturbations.
Skeleton Merger: an Unsupervised Aligned Keypoint Detector
In this paper, we propose an unsupervised aligned keypoint detector, Skeleton Merger, which utilizes skeletons to reconstruct objects.
PRIN/SPRIN: On Extracting Point-wise Rotation Invariant Features
Spherical Voxel Convolution and Point Re-sampling are proposed to extract rotation invariant features for each point.
Keypoint Autoencoders: Learning Interest Points of Semantics
Understanding point clouds is of great importance.
