Papers Style Transfer
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EndoLive: Real-Time Style Transfer for Endoscopic Endonasal Skull Base Surgical Video
Complex surgical procedures around critical anatomy, such as the endoscopic endonasal skull base surgery, requires significant practice and training on the part of the surgeon before they are allowed to perform the opera…
Style TransferRefDiT: Local Attribute Guidance in Reference-Based Image Generation
Personalization models generate new images guided by a few subject references, while style transfer methods aim to produce images aligned with a global style derived from a reference image. Recent approaches perform well…
Image GenerationStyle TransferCan Activation Steering Capture Multidimensional Authorship Style?
Activation steering has shown promise for controlling LLM generation along well-defined attributes, but it remains unclear whether it can handle the multidimensional and hard-to-define nature of authorship style. We ask …
Style TransferOne Editor, Many Edits: A Unified Training-Free Framework for Diverse Video Editing
Video editing spans diverse editing paradigms, yet achieving high-quality instruction-guided and subject-guided editing within a single unified framework remains challenging. We introduce EditVid, a training-free framewo…
Style TransferLoopy: Seamless Video Loop Generation via Anchored Looping Shift of Positional Embedding
Looping videos are essential for practical applications such as web graphics, game development, and social media. However, existing approaches typically fail to generate high-quality looping videos due to the neglect of …
Video GenerationStyle TransferSimple, Safe, and Overlooked: Reclaiming Sustainable Domain Generalization with Statistical Color Matching
Hardware shifts, color variations, and changing patient characteristics between development and deployment routinely break trained medical image classifiers. Existing remedies fall short: standard color jittering provide…
Domain GeneralizationData AugmentationStyle TransferAgainst Political Polarization: A Unified Framework for Tracing Evolving Political Ideologies on Social Media
The rapid growth of social media has greatly influenced political discourse, highlighting the need to understand individual political ideologies and their temporal dynamics. This task faces challenges such as data scarci…
Unsupervised Domain AdaptationStyle TransferLearning Music Style for Piano Arrangement Through Cross-Modal Bootstrapping
What is music style? Though often described using text labels such as "swing," "classical," or "emotional," the real style remains implicit and hidden in concrete music examples. In this paper, we introduce a cross-modal…
Contrastive LearningMusic GenerationStyle TransferProsody-driven Jailbreaks in Audio LLMs: A Controlled Study and Mechanistic Analysis
Audio-capable foundation models enable end-to-end spoken interaction, but they also introduce safety risks beyond transcript content. It remains unclear how much jailbreak capability can arise from matched-text variation…
Style TransferTrust Before Fusion: QIMG-7 and Source-Aware Resolution for Polluted Multimodal RAG
Multimodal retrieval-augmented generation (RAG) is often evaluated with clean evidence, yet real retrieval can return topically relevant but unreliable content: false text and misleading images from corrupted metadata, e…
Style TransferA Survey on LLM Watermarking: Theory and Deployment
Large language models (LLMs) are increasingly embedded in high-impact workflows, yet their ability to generate fluent text at scale has amplified risks of provenance ambiguity, model misuse, and large-scale content laund…
Style TransferEnhancing In-context Panoramic Generation via Geometric-aware Pretraining
In this work, we present Canvas360, a two-stage framework for in-context panoramic generation that combines geometry-aware pretraining with downstream task-specific fine-tuning. To address the lack of large-scale, high-q…
Style TransferMultimodal 3D LUT Generation via StatLUT with Statistical Features for Photorealistic Style Transfer
Photorealistic Style Transfer (PST) aims to transfer the color and tonal style of a reference to a content image while strictly preserving its structural integrity. However, existing deep learning-based methods inherentl…
Style TransferUnsupervised Domain Adaptation for Calcification Classification in Mammography Across Multi-Site Datasets
Deep learning-based computer-aided diagnosis (CAD) systems have shown strong performance in breast cancer diagnosis, particularly for classification tasks in mammography. However, domain shifts across multi-site datasets…
Unsupervised Domain AdaptationStyle TransferAnyStyle: A Single LoRA is Sufficient for Image-Guided Style Transfer
Image-guided style transfer aims to apply the artistic characteristics of a style image to a content image while preserving its semantic structure and layout. Despite advances in diffusion-based methods, existing approac…
Computational EfficiencyStyle TransferDICT: Data Injection and Contrastive Trajectory Refinement for Conditional Image Generation with Diffusion Models
Diffusion models have become a dominant paradigm for conditional image generation, yet existing approaches generally follow two directions: task-specific designs that can improve performance but limit generalization, and…
Conditional Image GenerationImage Super-ResolutionImage DeblurringStyle TransferNot All Prediction Targets Keep Training-Free Diffusion Guidance on the Manifold
Training-free guidance (TFG) steers a pretrained diffusion model toward a desired attribute at inference. To be effective, this guidance must be applied from the earliest, high-noise steps of sampling. Because its object…
Style TransferIlluminating Unified Multimodal Model for Free-form Interleaved Text-Image Generation
The advancement of generative AI models capable of producing text and image marks a critical step forward in the realm of multimodal intelligence, particularly for tasks involving the interleaving of both modalities. To …
Image GenerationStyle TransferASTAD: Asymmetric Style Transfer for Synthetic-to-Real Adaptation in Autonomous Driving
Synthetic data mitigates the data scarcity problem in autonomous driving perception. However, the synthetic-to-real gap leads to performance degradation, hindering real-world model generalization. Although current method…
Autonomous DrivingStyle TransferGeometry-Aware Style Transfer in 3D Gaussian Splatting
In this paper, we present a novel geometry-aware style transfer framework for 3D Gaussian splatting (3DGS) that simultaneously transfers appearance attributes and geometric structures. Unlike prior works that primarily f…
Style Transfer