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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 69
SpeeDiff: Scalable Pixel-Anchored End-to-End Latent Diffusion Model
We present Scalable Pixel-anchored End-to-end Diffusion (SpeeDiff), a latent diffusion method that jointly trains the VAE and the diffusion model from scratch.Towards Myocardial Infarction Diagnosis: An Investigation into Machine Learning and Deep Learning Algorithms using ECG Data
Myocardial Infarction (MI) is a severe and potentially fatal cardiac condition caused by myocardial injury due to ischemia, and timely detection can substantially reduce its mortality.Continual Learning Exam: Benchmarking Long-Horizon RSI and Experiential Learning in LLM Agents
Continual learning is the ability of LLM agents to improve over time by acquiring, refining, and applying knowledge from experience while retaining useful prior knowledge.Accuracy Is Not Enough: An Efficiency- and Statistics-Aware Benchmark of ResNet50 and Vision Transformer for Explainable Multi-Class Gastrointestinal Diseases Classification
Automated classification of gastrointestinal (GI) findings in endoscopic images could support early diagnosis, but architectures are often chosen on accuracy alone.InteractiveWorld: A Verifiable Human-Centric Environment for Building Better Interactive MLLM Assistants
People have long dreamed of an assistant that is always there to guide them and remind what they forget, from new dishes to lost keys.Hybrid Mamba-Transformer Network for Single-Shot 3D Reconstruction from Fringe Patterns
Deep learning facilitates rapid single shot three dimensional (3D) reconstruction using fringe projection profilometry (FPP), but recovering accurate surface height from a single high frequency…Explaining Navigation Decisions: Stage-Aware Visual Attribution for Vision-Language Navigation
As Vision-Language Models (VLMs) increasingly enable robots to follow language instructions, understanding their navigation decisions becomes important for reliable deployment.Fovea-JEPA: Overcoming Geometric Blind Spots in V-JEPA for Camera Motion Recognition
Camera motion recognition requires separating viewpoint changes caused by camera translation, rotation, or zoom from object motion and scene dynamics.What Sketches Tell Us about LVLMs: Conventions, Grounding, and Localisation
LVLM benchmarks tell us whether a model answers correctly, but not which visual conventions it has retained, nor where those conventions live.BEHAVIOR-Spatial Benchmark: Evaluating Spatial Understanding for Robotics
Robot tasks require grounding spatial language in physical scenes, but task success alone cannot establish whether spatial instructions are followed.Doppler-aided Position-Velocity Tracking of Hidden Objects using mmWave Radar
Safe indoor operation requires autonomous tracking of objects that are not directly visible to the robot.Learning the Autoregressive: Direct Score-Difference Estimation with Amortized Future Credit for Video Distillation
Few-step distillation for autoregressive (AR) video generation commonly first initializes an AR student and then refines it with distribution matching distillation (DMD).LegoOcc++: Towards Consistent Open-Vocabulary 3D Occupancy Prediction
Open-vocabulary 3D occupancy prediction is important for embodied agents operating in complex environments whose semantic categories extend beyond fixed taxonomies.RoboDuo: Attempt, Check and Atomic Recovery through Code for Vision-Language-Action Models
Vision-Language-Action (VLA) models map a language instruction and the current observation directly to actions, without checking whether the instruction has been completed.StickFigure: Enabling Pose-Only IoT Cameras for Privacy-Preserving Edge Vision
Indoor IoT cameras can support assisted living and activity-aware spaces, but exporting raw RGB frames raises privacy concerns by exposing facial, clothing, and household details that body-motion…Reversion, Retention, and Semantic Intervention: Measuring Functional Content in CLIP Fine-Tuning Deltas
Fine-tuning adapts pretrained models to new tasks, but identifying which weight changes support the resulting behavior remains difficult.MuSTEL: A Large-Scale Multilingual Synthetic Text-Line Image Dataset for OCR
Optical character recognition (OCR) systems depend strongly on the scale and diversity of their training data.Humans in Space: Can MLLMs Construct Human-Centric Spatial Understanding via Active Exocentric Exploration?
While Multimodal Large Language Models (MLLMs) excel at zero-shot reasoning, their spatial capabilities are primarily evaluated through static, passive observation.Reinforcement Learning for Adaptive Crowd Flow Control Using Dynamic Barriers
Crowd barriers are widely used to regulate pedestrian movement during large public events such as pilgrimages.Freeze What Is Settled, Cache What Is Smooth: Spatial Freezing Keeps Step Caching in Its Low-Error Regime
Instruction-based image editors built on diffusion transformers run tens of denoising steps.