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.
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Newest papers, page 3
GEKey: Learning Geodesic Eccentric 3D Keypoints via Self-Supervision
Point clouds represent 3D object geometry as sets of spatial coordinates.DEQ-Det: Dual Evidence Queries for Few-Shot Analog IC Device Detection
Detecting analog integrated circuit (IC) devices in layout images supports circuit analysis and inspection.ReferClaw: Disambiguating User Intent for Egocentric Assistance
Users of egocentric AI assistants often ask short, ambiguous questions whose intended referents cannot be uniquely resolved from video and dialogue history.InfMasking: A Unified Variational Framework for Synergistic Multimodal Learning
Multimodal models are expected to exploit synergistic information, that is, information available only when multiple modalities are observed together.FlyingDrones: A Dataset and Benchmark for Optical Flow Estimation from UAV motion
Optical flow is an important cue for drone analysis in aerial surveillance, airspace monitoring, and long-range target tracking, where motion remains informative when appearance is weak.AffineGS: Unlocking Accurate Geometry in 3DGS via Spatially Varying Affine Rectification
3D Gaussian Splatting (3DGS) has become the leading approach for photorealistic novel view synthesis, yet its geometric accuracy lags behind its visual quality.Fast and Accurate Hand Estimation in Pixels, Interaction and World Space
Monocular hand mesh estimators commonly predict rig parameters and project the mesh to obtain 2D keypoints.Selective Event Evidence and Persistent Temporal Priors for Event-Based Point Tracking
Event cameras enable tracking under fast motion and challenging illumination.Multimodal Information Interactions Bottleneck for Multimodal Self-Supervised Learning
Multimodal self-supervised learning is challenged by heterogeneity, unequal informativeness, and complex information interactions across multimodal data sources such as images, text, audio, and…Seeing Beyond the Next Step: World-Model-Guided Human-Like Navigation in Multi-Agent Scenes
Selecting a next motion in a populated scene is not just a matter of avoiding what is currently in the way: an action can be locally feasible yet drift onto the road instead of the crosswalk, cut…Comparing Classification and Feature Learning by Analyzing Their Loss Functions in Normalized Spaces with Different Scale Factors
Classification and feature learning are two closely interrelated fundamental tasks.BiGrounder: Bidirectional Training Unlocks the Potential of GUI Grounding
Graphical User Interface (GUI) grounding aims to map natural language instructions to precise operational coordinates, serving as a critical task for autonomous agent interaction.Adapters as Data: The Latent Space of LoRAs
LoRA adapters are usually treated as finished artifacts rather than as a data modality.Rain Beyond Streaks: Cascaded Realistic Rain and Wet Surface Synthesis via Scene Priors
Realistic rain synthesis is a persistent challenge for vision systems operating in adverse weather.Self-Supervised Diffusion Models for Handwritten Signature Verification via Ruin Reconstruction
Handwritten signature verification (HSV) is a critical biometric technique in legal and forensic authentication, whose efficacy hinges on the discriminability of signature representations.MV-Sign: Multi-View 3D Motion Integration and Enhanced Text-to-Motion Conditioning for Sign Language Production
Sign language production (SLP) aims to generate appropriate sign language motion from spoken language text.CMDiff: Left Atrial Scar Segmentation from 3D LGE MRI Using Conditional Mask Diffusion Model: A Feasibility Study
Late gadolinium enhancement (LGE) cardiac MRI enables non-invasive assessment of left atrial (LA) scar, an imaging marker associated with atrial fibrillation ablation outcome.STAG-Net: Structure-Aware Attention over Landmark Groups for Lightweight Head Pose Estimation
Head pose estimation is important for human computer interaction and driver monitoring, but many image based methods remain too costly for resource constrained deployment.THG-Omni: Traceable Human-Centric Graph Supervision for Video Reasoning
Omni-modal models can answer questions about video, but their predictions rarely show which participant, event, or interval supports an answer.Enhanced MRI brain tumor detection using deep learning in conjunction with explainable AI SHAP based diverse and multi feature analysis
Recent innovations in medical imaging have markedly improved brain tumor identification, surpassing conventional diagnostic approaches that suffer from low resolution, radiation exposure, and…