Papers Denoising
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fastWDM3D: Fast and Accurate 3D Healthy Tissue Inpainting
Healthy tissue inpainting has significant applications, including the generation of pseudo-healthy baselines for tumor growth models and the facilitation of image registration. In previous editions of the BraTS Local Syn…
3D InpaintingDenoisingImage GenerationImage Registration+1Diffuman4D: 4D Consistent Human View Synthesis from Sparse-View Videos with Spatio-Temporal Diffusion Models
This paper addresses the challenge of high-fidelity view synthesis of humans with sparse-view videos as input. Previous methods solve the issue of insufficient observation by leveraging 4D diffusion models to generate vi…
DenoisingGPUSimilarity-Guided Diffusion for Contrastive Sequential Recommendation
In sequential recommendation systems, data augmentation and contrastive learning techniques have recently been introduced using diffusion models to achieve robust representation learning. However, most of the existing ap…
Contrastive LearningData AugmentationDenoisingRecommendation Systems+2HUG-VAS: A Hierarchical NURBS-Based Generative Model for Aortic Geometry Synthesis and Controllable Editing
Accurate characterization of vascular geometry is essential for cardiovascular diagnosis and treatment planning. Traditional statistical shape modeling (SSM) methods rely on linear assumptions, limiting their expressivit…
DenoisingAirLLM: Diffusion Policy-based Adaptive LoRA for Remote Fine-Tuning of LLM over the Air
Operating Large Language Models (LLMs) on edge devices is increasingly challenged by limited communication bandwidth and strained computational and memory costs. Thus, cloud-assisted remote fine-tuning becomes indispensa…
DenoisingSequential Decision MakingA statistical physics framework for optimal learning
Learning is a complex dynamical process shaped by a range of interconnected decisions. Careful design of hyperparameter schedules for artificial neural networks or efficient allocation of cognitive resources by biologica…
DenoisingMeta-LearningLangMamba: A Language-driven Mamba Framework for Low-dose CT Denoising with Vision-language Models
Low-dose computed tomography (LDCT) reduces radiation exposure but often degrades image quality, potentially compromising diagnostic accuracy. Existing deep learning-based denoising methods focus primarily on pixel-level…
DenoisingDiagnosticImage ReconstructionMambaUnconditional Diffusion for Generative Sequential Recommendation
Diffusion models, known for their generative ability to simulate data creation through noise-adding and denoising processes, have emerged as a promising approach for building generative recommenders. To incorporate user …
DenoisingSequential RecommendationTranslationSPADE: Spatial-Aware Denoising Network for Open-vocabulary Panoptic Scene Graph Generation with Long- and Local-range Context Reasoning
Panoptic Scene Graph Generation (PSG) integrates instance segmentation with relation understanding to capture pixel-level structural relationships in complex scenes. Although recent approaches leveraging pre-trained visi…
DenoisingGraph GenerationInstance SegmentationPanoptic Scene Graph Generation+4ScoreAdv: Score-based Targeted Generation of Natural Adversarial Examples via Diffusion Models
Despite the success of deep learning across various domains, it remains vulnerable to adversarial attacks. Although many existing adversarial attack methods achieve high success rates, they typically rely on $\ell_{p}$-n…
Adversarial AttackDenoisingLeveraging the Spatial Hierarchy: Coarse-to-fine Trajectory Generation via Cascaded Hybrid Diffusion
Urban mobility data has significant connections with economic growth and plays an essential role in various smart-city applications. However, due to privacy concerns and substantial data collection costs, fine-grained hu…
DenoisingPrivacy PreservingHierarchical Intent-guided Optimization with Pluggable LLM-Driven Semantics for Session-based Recommendation
Session-based Recommendation (SBR) aims to predict the next item a user will likely engage with, using their interaction sequence within an anonymous session. Existing SBR models often focus only on single-session inform…
Contrastive LearningDenoisingSession-Based RecommendationsCoT-lized Diffusion: Let's Reinforce T2I Generation Step-by-step
Current text-to-image (T2I) generation models struggle to align spatial composition with the input text, especially in complex scenes. Even layout-based approaches yield suboptimal spatial control, as their generation pr…
DenoisingLarge Language ModelMultimodal Large Language ModelEnergy-Based Transformers are Scalable Learners and Thinkers
Inference-time computation techniques, analogous to human System 2 Thinking, have recently become popular for improving model performances. However, most existing approaches suffer from several limitations: they are moda…
DenoisingImage DenoisingMathFreeMorph: Tuning-Free Generalized Image Morphing with Diffusion Model
We present FreeMorph, the first tuning-free method for image morphing that accommodates inputs with different semantics or layouts. Unlike existing methods that rely on finetuning pre-trained diffusion models and are lim…
DenoisingImage MorphingRobuSTereo: Robust Zero-Shot Stereo Matching under Adverse Weather
Learning-based stereo matching models struggle in adverse weather conditions due to the scarcity of corresponding training data and the challenges in extracting discriminative features from degraded images. These limitat…
DenoisingDepth EstimationDisparity EstimationStereo Matching+1Score-Based Model for Low-Rank Tensor Recovery
Low-rank tensor decompositions (TDs) provide an effective framework for multiway data analysis. Traditional TD methods rely on predefined structural assumptions, such as CP or Tucker decompositions. From a probabilistic …
DenoisingEAMamba: Efficient All-Around Vision State Space Model for Image Restoration
Image restoration is a key task in low-level computer vision that aims to reconstruct high-quality images from degraded inputs. The emergence of Vision Mamba, which draws inspiration from the advanced state space model M…
AllDeblurringDenoisingImage Restoration+2SmoothSinger: A Conditional Diffusion Model for Singing Voice Synthesis with Multi-Resolution Architecture
Singing voice synthesis (SVS) aims to generate expressive and high-quality vocals from musical scores, requiring precise modeling of pitch, duration, and articulation. While diffusion-based models have achieved remarkabl…
DenoisingSinging Voice SynthesisVideo GenerationIntegrating Vehicle Acoustic Data for Enhanced Urban Traffic Management: A Study on Speed Classification in Suzhou
This study presents and publicly releases the Suzhou Urban Road Acoustic Dataset (SZUR-Acoustic Dataset), which is accompanied by comprehensive data-acquisition protocols and annotation guidelines to ensure transparency …
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