arXiv:2604.20730v3 Announce Type: replace Abstract: Multimodal Large Language Models (MLLMs) have shown promising capabilities in generating Scalable Vector Graphics (SVG) via direct code synthesis. However, existing…
arXiv:2607.09067v1 Announce Type: new Abstract: Text-to-image diffusion models exhibit unprecedented generative capability and contain rich intermediate representations that can be useful for discriminative vision tasks. Motivated…
arXiv:2601.09881v2 Announce Type: replace Abstract: Large video diffusion and flow models have achieved remarkable success in high-quality video generation, but their use in real-time interactive applications…
arXiv:2607.09061v1 Announce Type: new Abstract: A striking feature of the human visual system is that it ingests visual information through a series of local foveated glimpses,…
arXiv:2504.15650v3 Announce Type: replace Abstract: Building a generalized affordance grounding model to identify actionable regions on objects is vital for real-world applications. Existing methods to train…
arXiv:2607.09057v1 Announce Type: new Abstract: Cross-view geo-localization (CVGL) aims to achieve GPS-free localization by matching drone-view images with corresponding satellite-view images. Existing supervised methods rely on…
arXiv:2607.09029v1 Announce Type: new Abstract: Vision-Language Models (VLMs) have achieved success using homogeneous Transformers to process multimedia data. Recent studies show that heterogeneous structures interleaving efficient…
arXiv:2607.09657v1 Announce Type: new Abstract: The rapid progress of large foundation models has been driven predominantly by pretraining on large-scale text corpora. However, many forms of…
arXiv:2607.09024v1 Announce Type: new Abstract: Driven by next-token prediction, NLP shifted from task-specific models into powerful generalist foundation models. What, then, is the equivalent catalyst needed…
arXiv:2607.09630v1 Announce Type: new Abstract: Collecting annotated plant images for automated phenotyping is often slow and expensive. Plant models simulating growth and development can generate unlimited…
arXiv:2607.08867v1 Announce Type: new Abstract: Cloud-based deep learning enables large-scale medical image analysis but raises significant privacy concerns when sensitive patient images are outsourced for model…
arXiv:2607.08879v1 Announce Type: new Abstract: Indoor scene relighting demands photorealism, precise spatial control, and strict multi-view consistency. While diffusion-based image editing models enable semantic lighting manipulation…
arXiv:2607.08896v1 Announce Type: new Abstract: We describe our entry to the ICIP 2026 Grand Challenge on Extreme In-the-Wild License Plate Super-Resolution (XLPSR), which scored 9.73 wECR…
arXiv:2607.08945v1 Announce Type: new Abstract: Accurate cocoa mapping is increasingly important for deforestation monitoring, supply-chain transparency, and regulatory applications. Spatial aggregation in conventional medium-resolution Earth observation…
arXiv:2607.08932v1 Announce Type: new Abstract: Figure-ground organization in the human visual system relies on several shape-based cues, including surroundedness, convexity, and symmetry. While these cues have…
arXiv:2607.09008v1 Announce Type: new Abstract: Safety-critical perception systems must reliably detect rare object classes within small label spaces, a setting that long-tailed detection methods, designed for…
arXiv:2607.08970v1 Announce Type: new Abstract: Recent benchmarks for VLMs largely assess single- or limited-view perception, leaving untested the core cognitive ability to integrate observations across viewpoints…
arXiv:2412.02983v2 Announce Type: replace Abstract: Few-shot Semantic Segmentation (FSS) aims to adapt a pre-trained model to new classes with as few as a single labeled training…
arXiv:2607.09102v1 Announce Type: cross Abstract: Medical imaging models are often deployed without the demographic, acquisition, and quality metadata needed for subgroup auditing. Once those metadata disappear,…
arXiv:2603.21309v3 Announce Type: replace Abstract: Facial expression recognition (FER) in videos requires model personalization to capture considerable variations across subjects. Vision-language models (VLMs) offer strong transfer…
arXiv:2510.15849v3 Announce Type: replace Abstract: Accurate tongue segmentation is crucial for reliable TCM analysis. Supervised models require large annotated datasets, while SAM-family models remain prompt-driven. We…
arXiv:2603.23086v2 Announce Type: replace-cross Abstract: Autoregressive (AR) models are highly effective for image generation, yet their standard maximum-likelihood estimation training lacks direct optimization for sample quality…
arXiv:2606.31513v2 Announce Type: replace Abstract: Single-image reflection removal (SIRR) seeks to recover the transmission layer from a mixture corrupted by reflections -- a severely ill-posed problem.…
arXiv:2607.09562v1 Announce Type: new Abstract: Medical Vision-Language Models (VLMs) exhibit strong zero-shot performance, yet their effectiveness still declines on out-of-distribution (OOD) data due to domain shifts…