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Found 20 papers, 7 papers with code
DSM: Building A Diverse Semantic Map for 3D Visual Grounding
This method leverages VLMs to capture the latent semantic attributes and relations of objects within the scene and creates a Diverse Semantic Map (DSM) through a geometry sliding-window map construction strategy.
SPF-Portrait: Towards Pure Portrait Customization with Semantic Pollution-Free Fine-tuning
Fine-tuning a pre-trained Text-to-Image (T2I) model on a tailored portrait dataset is the mainstream method for text-driven customization of portrait attributes.
HumanAesExpert: Advancing a Multi-Modality Foundation Model for Human Image Aesthetic Assessment
Image Aesthetic Assessment (IAA) is a long-standing and challenging research task.
NuGrounding: A Multi-View 3D Visual Grounding Framework in Autonomous Driving
Multi-view 3D visual grounding is critical for autonomous driving vehicles to interpret natural languages and localize target objects in complex environments.
Diffusion Suction Grasping with Large-Scale Parcel Dataset
While recent advances in object suction grasping have shown remarkable progress, significant challenges persist particularly in cluttered and complex parcel handling scenarios.
DreamFit: Garment-Centric Human Generation via a Lightweight Anything-Dressing Encoder
However, existing methods often face a dilemma: lightweight approaches, such as adapters, are prone to generate inconsistent textures; while finetune-based methods involve high training costs and struggle to maintain the generalization capabilities of pretrained diffusion models, limiting their performance across diverse scenarios.
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.
Constraint Learning for Parametric Point Cloud
Stage 1 extracts constraints from B-Rep data or point cloud.
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.
Automated Peer Reviewing in Paper SEA: Standardization, Evaluation, and Analysis
Finally, SEA-A introduces a new evaluation metric called mismatch score to assess the consistency between paper contents and reviews.
GaussianRoom: Improving 3D Gaussian Splatting with SDF Guidance and Monocular Cues for Indoor Scene Reconstruction
Embodied intelligence requires precise reconstruction and rendering to simulate large-scale real-world data.
SD-Net: Symmetric-Aware Keypoint Prediction and Domain Adaptation for 6D Pose Estimation In Bin-picking Scenarios
Specifically, at the keypoint prediction stage, we designe a robust 3D keypoints selection strategy considering the symmetry class of objects and equivalent keypoints, which facilitate locating 3D keypoints even in highly occluded scenes.
NormNet: Scale Normalization for 6D Pose Estimation in Stacked Scenarios
Existing Object Pose Estimation (OPE) methods for stacked scenarios are not robust to changes in object scale.
Medical Image Segmentation via Sparse Coding Decoder
Transformers have achieved significant success in medical image segmentation, owing to its capability to capture long-range dependencies.
3DFill:Reference-guided Image Inpainting by Self-supervised 3D Image Alignment
We then fill the hole in the target image with the contents of the aligned image.
PCKRF: Point Cloud Completion and Keypoint Refinement With Fusion Data for 6D Pose Estimation
In this paper, we propose Point Cloud Completion and Keypoint Refinement with Fusion Data (PCKRF), a new pose refinement pipeline for 6D pose estimation.
Class-Aware Contrastive Semi-Supervised Learning
Pseudo-label-based semi-supervised learning (SSL) has achieved great success on raw data utilization.
PPR-Net:Point-wise Pose Regression Network for Instance Segmentation and 6D Pose Estimation in Bin-picking Scenarios
For each point in the point cloud, the network regresses a 6D pose of the object instance that the point belongs to.
SpiderCNN: Deep Learning on Point Sets with Parameterized Convolutional Filters
Deep neural networks have enjoyed remarkable success for various vision tasks, however it remains challenging to apply CNNs to domains lacking a regular underlying structures such as 3D point clouds.
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