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: 4,996 arXiv preprints and 4 OpenAlex records.
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 233
GroundingPI: A Grounding Foundation Model towards Physical Intelligence with Visual Primitives
Precise grounding matters.FOMO: Forget the Concept, Don't Miss Out on the Scene in Selective Video Unlearning
The rapid advancement of generative video models has enabled the synthesis of increasingly realistic and temporally coherent videos, while also raising concerns about the generation of harmful…Semantic Watermarking for Malicious Image Manipulation Detection
The proliferation of high-fidelity generative editing models has made it possible to inject violent or sexual content into otherwise ordinary images while preserving visual plausibility, with…ExpandDiff: Dynamic Range Expanding Diffusion for Single-Image HDR Reconstruction
Single-image HDR reconstruction requires inferring missing detail while preserving the visible content of an LDR image.D-Scope: Decomposing and Steering Diffusion Transformers with Sparse Autoencoders
Sparse autoencoders (SAEs) reveal visual structure in diffusion transformers (DiTs), but interpreting a feature does not establish whether it can be used to control generation.Introduction to Computer Vision
This book presents a code-first introduction to computer vision, spanning classical 2D image processing, classical 3D vision, and deep learning.SAGE: Salient Factor Discovery and Generation with Visual Foundation Representations
Given a target dataset, such as faces with eyeglasses, and a background dataset, such as faces without, contrastive analysis separates \textit{salient} factors specific to the target from…From Modes to Memories: Characterizing the Scale-Space Dynamics of Diffusion Models
Diffusion models are typically viewed as stochastic processes that transform noise into data.FANVIDv2: Evaluating Video Super-Resolution by Face and Licence-Plate Recognition Under Compound Degradation
Video super-resolution (VSR) is normally judged by PSNR and SSIM on clips that were downsampled bicubically, although in surveillance its purpose is to make faces and licence plates…Diffusable Latents from Structure-Agnostic Distillation
Distilling pretrained foundation models into an autoencoder bottleneck improves latent diffusability, enabling diffusion models to converge faster and reach higher sample quality.BAM! Bayesian Anything Model: a foundation model for generative computational imaging
Generative models are transforming Bayesian computational imaging, yet the field still lacks physics-aware foundation models.Typographic Attack Against VLM-based AI-generated Image Detection
Vision-language models (VLMs) are increasingly used for AI-generated image (AIGI) detection, providing natural-language explanations for authenticity judgments.MC-PanDA++: Simpler, Stronger, and More Robust Domain-Adaptive Panoptic Segmentation
Unsupervised domain adaptation (UDA) reduces the annotation burden in panoptic segmentation by leveraging a cost-effectively labeled source domain (e.g., synthetic) and an unlabeled target domain to…Unapologetically Distributed: A Call for Decentralized Document Analysis
Privacy has become an increasingly important concern in the Document Analysis community, to the extent that in many environments such as archives, governmental institutions, and local businesses…ShieldCLIP: Selective Safety Alignment for Harmful Content Mitigation in Multimodal Foundation Models
Multimodal encoders such as CLIP underlie many downstream systems, but their web-scale training data embed harmful associations that safety alignment must suppress without unnecessarily changing…When Masking Helps or Hurts Robustness in Compressed CLIP: A Pre-Deployment Diagnostic
This paper demonstrate that whether masking-based token pruning helps or hurts worst-group robustness can be predicted before deployment, without labels or fine-tuning.BTC3D: Blended Tile Conditioning for Detail-Enhancing Image-to-3D Generation
Recent diffusion-based pipelines have achieved promising progress in image-to-3D synthesis.Let the Carrier Carry the Attack: Preserving the Subject in Adversarial Image Generation
Strong unrestricted adversarial attacks can distort the primary object of an image, hereafter referred to as the subject.FAST: Flow Any Scene Transformer
Scaling has become a primary driver of progress in language and vision foundation models, yet its role in precise correspondence matching remains underexplored.Determining Vertical Displacement of Agricultural Areas Using UAV-Photogrammetry and a Heteroscedastic Deep Learning Model
This article introduces an algorithm that uses a U-Net architecture to determine vertical ground surface displacements from unmanned aerial vehicle (UAV)-photogrammetry point clouds, offering an…