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Found 23 papers, 10 papers with code
KAN or MLP? Point Cloud Shows the Way Forward
To overcome the high parameter counts and computational inefficiency of standard KANs, we develop Efficient-KANs in the PointKAN-elite variant, which significantly reduces parameters while maintaining accuracy.
UniCombine: Unified Multi-Conditional Combination with Diffusion Transformer
With the rapid development of diffusion models in image generation, the demand for more powerful and flexible controllable frameworks is increasing.
PixelPonder: Dynamic Patch Adaptation for Enhanced Multi-Conditional Text-to-Image Generation
Recent advances in diffusion-based text-to-image generation have demonstrated promising results through visual condition control.
DynamicControl: Adaptive Condition Selection for Improved Text-to-Image Generation
To enhance the controllability of text-to-image diffusion models, current ControlNet-like models have explored various control signals to dictate image attributes.
Unveil Inversion and Invariance in Flow Transformer for Versatile Image Editing
Leveraging the large generative prior of the flow transformer for tuning-free image editing requires authentic inversion to project the image into the model's domain and a flexible invariance control mechanism to preserve non-target contents.
FitDiT: Advancing the Authentic Garment Details for High-fidelity Virtual Try-on
Although image-based virtual try-on has made considerable progress, emerging approaches still encounter challenges in producing high-fidelity and robust fitting images across diverse scenarios.
Ranked #1 on
Virtual Try-on
on VITON-HD
MureObjectStitch: Multi-reference Image Composition
Generative image composition aims to regenerate the given foreground object in the background image to produce a realistic composite image.
Typicalness-Aware Learning for Failure Detection
We observe that, with the cross-entropy loss, model predictions are optimized to align with the corresponding labels via increasing logit magnitude or refining logit direction.
Mamba-YOLO-World: Marrying YOLO-World with Mamba for Open-Vocabulary Detection
However, its performance is hindered by its neck feature fusion mechanism, which causes the quadratic complexity and the limited guided receptive fields.
DualAnoDiff: Dual-Interrelated Diffusion Model for Few-Shot Anomaly Image Generation
In this paper, we overcome these challenges from a new perspective, simultaneously generating a pair of the overall image and the corresponding anomaly part.
MM-Tracker: Motion Mamba with Margin Loss for UAV-platform Multiple Object Tracking
To address these issues, we propose the Motion Mamba Module, which explores both local and global motion features through cross-correlation and bi-directional Mamba Modules for better motion modeling.
A Comprehensive Library for Benchmarking Multi-class Visual Anomaly Detection
This paper addresses this issue by proposing a comprehensive visual anomaly detection benchmark, ADer, which is a modular framework that is highly extensible for new methods.
NoiseBoost: Alleviating Hallucination with Noise Perturbation for Multimodal Large Language Models
Multimodal large language models (MLLMs) contribute a powerful mechanism to understanding visual information building on large language models.
AdapNet: Adaptive Noise-Based Network for Low-Quality Image Retrieval
To mitigate this issue, we introduce a novel setting for low-quality image retrieval, and propose an Adaptive Noise-Based Network (AdapNet) to learn robust abstract representations.
PointRWKV: Efficient RWKV-Like Model for Hierarchical Point Cloud Learning
Transformers have revolutionized the point cloud learning task, but the quadratic complexity hinders its extension to long sequence and makes a burden on limited computational resources.
Open-Vocabulary SAM3D: Towards Training-free Open-Vocabulary 3D Scene Understanding
This framework is designed to perform understanding tasks for any 3D scene without requiring prior knowledge of the scene.
Leveraging Fine-Grained Information and Noise Decoupling for Remote Sensing Change Detection
Next, a shape-aware and a brightness-aware module are designed to improve the capacity for representation learning.
Single-temporal Supervised Remote Change Detection for Domain Generalization
In this paper, we propose a multimodal contrastive learning (ChangeCLIP) based on visual-language pre-training for change detection domain generalization.
MambaAD: Exploring State Space Models for Multi-class Unsupervised Anomaly Detection
Recent advancements in anomaly detection have seen the efficacy of CNN- and transformer-based approaches.
PointSeg: A Training-Free Paradigm for 3D Scene Segmentation via Foundation Models
On top of that, PointSeg can incorporate with various foundation models and even surpasses the specialist training-based methods by 3. 4$\%$-5. 4$\%$ mAP across various datasets, serving as an effective generalist model.
UniM-OV3D: Uni-Modality Open-Vocabulary 3D Scene Understanding with Fine-Grained Feature Representation
3D open-vocabulary scene understanding aims to recognize arbitrary novel categories beyond the base label space.
Stereo RGB and Deeper LIDAR Based Network for 3D Object Detection
After aligning the interior points with fused features, the proposed network refines the prediction in a more accurate manner and encodes the whole box in a novel compact method.
SVGA-Net: Sparse Voxel-Graph Attention Network for 3D Object Detection from Point Clouds
Accurate 3D object detection from point clouds has become a crucial component in autonomous driving.
Ranked #1 on
3D Object Detection
on KITTI Pedestrians Hard
