AI & Machine Learning · Computer Science & AI
Computer Vision
The newest papers in Computer Vision that ReadSearch has read, newest first. Each links to its own page, with its authors, date, where it was published and the original.
The newest 5,000 papers, from 29 September 2026 to 5 November 2026: 4,999 arXiv preprints and 1 OpenAlex record.
Get the few papers worth your time in Computer Vision every morning.
Follow Computer Vision and ReadSearch reads its new papers each day, then brings you the few worth reading, each with its key finding in a sentence.
Newest papers, page 75
RelateGS: Reliable Semantic and Relational Evidence for 3D Scene Understanding with Gaussian Splatting
Language-aware 3D Gaussian Splatting (3DGS) has advanced language-driven 3D scene understanding by incorporating semantic and relational cues into reconstructed scenes.Stable Dimensionality Reduction via Isometric Centroid-Encoder
Many supervised dimensionality reduction methods promote intra-class compactness and inter-class separation but do not explicitly constrain class geometry, leading to variability in the relative…Semantic Concept Steering Breaks the Explanation Drift Loop in Continual Learning
Catastrophic forgetting in continual learning (CL) manifests not only as accuracy degradation but also as \emph{explanation drift}: models maintain predictive accuracy while silently shifting…WMEval: Evaluating Interactive World Models Grounded on Physical Simulations
Interactive world models hold immense potential for high-stakes applications in robotics, game engines, and immersive digital twins, yet existing benchmarks primarily focus on perceptual similarity…Rank-1 Weight-Corrected Trainable Weight Averaging for Out-of-Distribution Detection
Out-of-distribution (OOD) detection identifies inputs outside the training distribution.Texture-Aware Strategies for Subregion Style Transfer Augmentation
A common strategy for data augmentation is to apply style transfer on training images to enrich appearance variations.TurboWAM: Learning What Matters for Fast World Action Models
World action models have demonstrated promising performance in robot policy learning, yet their high inference latency remains a critical bottleneck for real-world deployment.MAGIC: Margin-gated Contrastive Debiasing with Evidence Restoration for VLM Test-time Robustness Scaling
This paper studies the problem of test-time robustness scaling for large vision-language models (LVLMs), which aims to mitigate language bias during inference.Rethinking Representation Geometry in Supervised Contrastive Learning under Long-Tailed Data
Supervised contrastive learning and its balanced variants have demonstrated their effectiveness for representation learning under long-tailed distributions.NUViT: Vision Transformers for Fourier Space Data
Vision Transformers (ViTs) have demonstrated strong performance in many computer vision tasks but do not naturally extend beyond the natural image domain.X-Dubbing: Speech-to-Speech Translation under Temporal and Visual Constraints
Cross-lingual dubbing aims to convert source speech into target-language speech that remains synchronized with the original video.ACVA-Bench: Beyond Prompt Following in Abstract Concept Visualization Ability for Text-to-Image Models
Text-to-image (T2I) models have achieved remarkable progress in image quality and instruction following, prompting growing research interest in their capacity for deep understanding that goes beyond…Concept Acupuncturist: An Efficient and Precise Concept Erasure Method for Diffusion Models via Sparse Autoencoders
Diffusion-based image generation models produce high-quality images but may generate harmful or policy-violating content, motivating machine unlearning (MU) to selectively remove target concepts…Guided Zero-Shot Anomaly Explanation for Anonymized Crowd Video Monitoring: Context, Categorization, and Spatial Localization
Despite the promising development of deep learning for video anomaly detection (VAD), explainability (XAI) of these models remains a challenge.RADIANT: Object-Centric Feed-Forward Global Illumination
Feed-forward neural renderers synthesize global illumination across novel 3D scenes without per-scene optimization or runtime ray tracing.TTT in VLA Models: Exploring Training with Human Demonstrations
Long-horizon robot tasks require retaining and using past information.ImageRSI: Verification-Driven Recursive Self-Improvement for Agentic Image Generation
Complex text-to-image requests remain difficult to satisfy reliably.Data Quality in RVL-CDIP: A Systematic Audit
RVL-CDIP is the de facto standard benchmark for document classification, and reported accuracy on it is now 98.8%.SyncPro: Synchronous Reasoning and Responding for Proactive Streaming Video Understanding
Proactive streaming video understanding requires assistants to track unfolding events and respond when a user's requested condition is met.Separating Angular Alignment from Radial Ordering in Hyperbolic Vision-Language Models
Hyperbolic vision-language models are well suited to modeling the hierarchical structure of multimodal data, because hyperbolic volume grows exponentially with radius, enabling low-distortion…