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Found 21 papers, 9 papers with code
AnyDressing: Customizable Multi-Garment Virtual Dressing via Latent Diffusion Models
Additionally, we introduce a Garment-Enhanced Texture Learning strategy to improve the fine-grained texture details of garments.
2DGS-Room: Seed-Guided 2D Gaussian Splatting with Geometric Constrains for High-Fidelity Indoor Scene Reconstruction
In this paper, we introduce 2DGS-Room, a novel method leveraging 2D Gaussian Splatting for high-fidelity indoor scene reconstruction.
Fine-detailed Neural Indoor Scene Reconstruction using multi-level importance sampling and multi-view consistency
Recently, neural implicit 3D reconstruction in indoor scenarios has become popular due to its simplicity and impressive performance.
UW-SDF: Exploiting Hybrid Geometric Priors for Neural SDF Reconstruction from Underwater Multi-view Monocular Images
Due to the unique characteristics of underwater environments, accurate 3D reconstruction of underwater objects poses a challenging problem in tasks such as underwater exploration and mapping.
Training-Free Point Cloud Recognition Based on Geometric and Semantic Information Fusion
For the geometric branch, we adopt a non-parametric strategy to extract geometric features.
Freehand Sketch Generation from Mechanical Components
To address this issue, we design a two-stage generative framework mimicking the human sketching behavior pattern, called MSFormer, which is the first time to produce humanoid freehand sketches tailored for mechanical components.
RegionDrag: Fast Region-Based Image Editing with Diffusion Models
However, point-drag-based approaches suffer from computational overhead and misinterpretation of user intentions due to the sparsity of point-based editing instructions.
GaussianRoom: Improving 3D Gaussian Splatting with SDF Guidance and Monocular Cues for Indoor Scene Reconstruction
However, when it comes to indoor scenes with a significant number of textureless areas, 3DGS yields incomplete and noisy reconstruction results due to the poor initialization of the point cloud and under-constrained optimization.
When LLMs step into the 3D World: A Survey and Meta-Analysis of 3D Tasks via Multi-modal Large Language Models
Hence, with this paper, we aim to chart a course for future research that explores and expands the capabilities of 3D-LLMs in understanding and interacting with the complex 3D world.
GenesisTex: Adapting Image Denoising Diffusion to Texture Space
We present GenesisTex, a novel method for synthesizing textures for 3D geometries from text descriptions.
Enhancing Industrial Transfer Learning with Style Filter: Cost Reduction and Defect-Focus
Addressing the challenge of data scarcity in industrial domains, transfer learning emerges as a pivotal paradigm.
GaussCtrl: Multi-View Consistent Text-Driven 3D Gaussian Splatting Editing
We propose GaussCtrl, a text-driven method to edit a 3D scene reconstructed by the 3D Gaussian Splatting (3DGS).
Consensus Focus for Object Detection and minority classes
Ensemble methods exploit the availability of a given number of classifiers or detectors trained in single or multiple source domains and tasks to address machine learning problems such as domain adaptation or multi-source transfer learning.
SD4Match: Learning to Prompt Stable Diffusion Model for Semantic Matching
In this paper, we address the challenge of matching semantically similar keypoints across image pairs.
SimSC: A Simple Framework for Semantic Correspondence with Temperature Learning
This module is trained together with the backbone and the temperature is updated online.
Robust Ellipsoid Fitting Using Axial Distance and Combination
Subsequently, a novel sample-consensus-based ellipsoid fitting method is proposed by using the combination between the axial distance and Sampson distance (CAS).
Neural Refinement for Absolute Pose Regression with Feature Synthesis
To enhance the robustness of our model, we introduce a feature fusion module and a progressive training strategy.
Model-based Transfer Learning for Automatic Optical Inspection based on domain discrepancy
However, related research enhanced the network models by applying TL without considering the domain similarity among datasets, the data long-tailedness of a source dataset, and mainly used linear transformations to mitigate the lack of samples.
Disentangling 3D Attributes from a Single 2D Image: Human Pose, Shape and Garment
Specifically, we focus on human appearance and learn implicit pose, shape and garment representations of dressed humans from RGB images.
DFNet: Enhance Absolute Pose Regression with Direct Feature Matching
We introduce a camera relocalization pipeline that combines absolute pose regression (APR) and direct feature matching.
Dual-Resolution Correspondence Networks
The fine-resolution feature maps are used to obtain the final dense correspondences guided by the refined coarse 4D correlation tensor.
