Computer Vision

Researchers propose sub-semantic image segmentation, a new category that partitions images into stable appearance patterns described by language rather than naming whole objects. They introduce DETECTURE, a system that o…

Researchers introduced FairGen, a fairness-aware diffusion framework that synthesizes demographically balanced medical images while preserving pathology-relevant features. Applied to dermatology, radiology, and neuroimag…

Researchers from an undisclosed institution introduced Convolutional Nearest Neighbors (ConvNN), a unified framework that shows convolution and self-attention are special cases of k-nearest neighbor aggregation. ConvNN c…

Researchers introduced RAMS, a runtime controller that dynamically switches between YOLOv8 model tiers on embedded devices to balance latency and detection quality under resource pressure. On Jetson Orin TensorRT under h…

Researchers introduced VigilFormer, a video anomaly detection framework combining deformable spatio-temporal attention with causal temporal modeling, achieving state-of-the-art AUC scores of 87.83% on UCF-Crime, 97.21% o…

Researchers proposed a sub-quadratic vision transformer for image captioning that replaces standard self-attention with a Gaussian Mixture Model-based clustering mechanism, reducing computational complexity from O(n^2) t…

Researchers evaluated six deep learning architectures for maritime object detection, including CNNs and a Vision Transformer (ViT), using a dataset of 6,468 images under various weather conditions. The ViT achieved 100% …

Researchers introduced an LLM-driven framework for retrieving remote sensing data from cloud-based geospatial catalogues using natural language queries. The system uses three agents—Guardrail, General-QA, and Recommender…

Researchers introduced disagreement-based cross-model routing for implicit video question answering, achieving a +1.43 AvgAcc improvement on the ImplicitQA benchmark by routing disputed questions from Gemini 3.1 Pro Prev…

Researchers introduced a foundation model-driven framework for cross-modal representation alignment between CT imaging and longitudinal EHR data, improving time-to-event prediction across tasks and institutions. Fusion s…

Researchers developed a high-throughput 3D behavioral phenotyping framework integrating deep learning object detection with binocular stereo vision for real-time monitoring of juvenile tilapia. The system automates body …

Researchers propose Visual-Seeker, a multimodal deep search agent that actively reasons over visual details to perform multi-hop, cross-modal search. The agent achieves state-of-the-art results on five benchmarks, surpas…

Researchers introduced AgentViSS, a benchmark for evaluating visual social intelligence in multimodal agents, featuring 240 scenarios and four role-level tasks. Tests on seven multimodal large language models revealed th…

Researchers introduced the Membership Inference Test (MINT) Demo 2, a framework to detect whether specific data were used in training machine learning models, achieving up to 90% accuracy in tests on face recognition mod…

Researchers introduced MMLongEmbed, the first comprehensive benchmark for evaluating multimodal embedding models in long-context scenarios. The benchmark includes four retrieval tasks across text, document, and video mod…

Researchers propose Style-CCL, a multi-stage curriculum continual learning framework for content-preserving style transfer using Diffusion Transformers. The method trains a dual-branch SC-DiT from semantic to texture sty…

Researchers introduced HorusEye, a framework using language as dynamic attention for emergency visual analysis, and benchmarked it on the RefCOCO-Degraded dataset. Testing multiple vision-language models, they found Gemi…

Researchers introduced GridVQA-X, a diagnostic framework to evaluate cross-modal explainability in Vision-Language Models. The framework uses synthetic data with ground-truth explanations to test whether explainability m…

Researchers introduced UtVAA, an ultra-tiny Vision Transformer architecture with a novel Affix Attention block for mobile image classification. The smallest variant has 204.67K parameters and 53.95M FLOPs, achieving comp…

Researchers propose Steady-Forcing, a memory and training framework for autoregressive video diffusion models that balances spatial persistence and motion continuity in long-horizon nature video generation. The method im…