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 48
NeurEO: dissecting Earth observation embeddings with computational neuroscience
Earth embeddings are compressed representations of rich Earth observation data that enable downstream models to tackle a wide range of complex geospatial tasks.Hierarchical Step Decomposition for Training-free Online Video Step Grounding
Given a set of procedural steps, Video Step Grounding (VSG) aims to identify which steps occur in a video and localize when they are performed.EventSeeColor: Learning to Reconstruct Color from Monochrome Events
Event cameras capture visual brightness changes under challenging lighting conditions.Beyond CCT: Multi-channel SPD recovery for per-shot camera color correction
Modern cameras correct color via two or three pre-calibrated 3x3 matrices interpolated by Correlated Color Temperature (CCT).AdMuse: Skill-Guided Creative Advertising Image Generation
An outstanding creative advertising image should both attract attention and communicate a product's positioning.Video Generation Meets Agent Harness: Agentic Video Generation, Agentic World Modeling and Recursive Self-Improvement
Video generation is shifting from end-to-end synthesis toward agentic generation, where planning, tool use, and feedback enable coherent, controllable multi-shot videos.Decision-Level Error Attribution and Depth-Aware Safety Evaluation of Monocular RGB Human Tracking for Autonomous Robot Navigation
Monocular RGB tracking is useful for robots operating near people, but perception errors affect binary stop/proceed decisions in ways that geometric accuracy metrics do not capture.Benchmarking color judgment in multimodal LLMs with CIE-computable ground truth
Multimodal large language models (MLLMs) are now used as zero-shot judges of image quality, but their color judgments are rarely tested with colorimetric ground truth.TaskFrame: Connecting Task-Level Planning with Frame-Level Control for Game Agents
Building general game agents requires both high-level task reasoning and low-latency action control in rapidly changing visual environments.LoRe-MIM: Lost-or-Replaced Masked Image Modeling for Self-Supervised Representation Learning in Whole-Body PET/CT
Deep learning models for whole-body positron emission tomography/computed tomography (PET/CT) hold significant clinical potential for disease detection, treatment planning, and response assessment.Self-training for cross-centre coronary vessel segmentation in X-ray angiography using pre-contrast frame subtraction
Deep learning models for coronary vessel segmentation in X-ray angiography often perform poorly on data from centres that were not represented in training.Textual Response-Aware Guidance for Zero-Shot Adversarial Robustness of Vision-Language Models
Vision-language models (VLMs) exhibit strong zero-shot generalization but remain vulnerable to adversarial attacks.Radiology Guideline-derived Decision Graph for Efficient Clinical Decision Support
Radiological risk stratification and management planning are essential downstream tasks in medical imaging.RFW-A: Agentic Procedural Generation of 400K Articulated Assets over 500 Categories
High-quality articulated assets are essential for embodied perception, simulation, and manipulation, yet constructing them at scale remains difficult.Wizard: Manipulate Any World in Real Time via Agentic Control
Recent advances in video world models have enabled the generation of increasingly realistic and interactive virtual environments, opening new possibilities for player-customizable gameplay.HiFOR: Hierarchical Foresight with Action-Guided World Grounding for Vision-Language-Action Model
Vision-Language-Action (VLA) models have demonstrated promising capabilities in robotic manipulation by integrating visual perception, language understanding, and action generation.Continuous-Action World Models: Learning Cross-Embodiment Spatiotemporal Dynamics Priors
We introduce Continuous-Action World Models (CoAWM), a framework for learning cross-embodiment spatiotemporal dynamics priors that support robot action generation across embodiments and execution…Uncertainty-aware Feedback Loop Diagnosis: integrating reinforcement learning and conformal prediction for reliable wafer defect classification
Semiconductor manufacturing is a complex, multi-step process that requires both high precision and low operating costs.Soil Moisture Estimation in Precision Agriculture: A Knowledge Distillation Approach
Accurate soil moisture estimation is critical for precision agriculture, influencing irrigation, fertilization, and harvesting strategies.PhysInsert: Physically Plausible Object Insertion with Geometric Priors and Bidirectional Object-Scene Interactions
We present PhysInsert, a framework for physically plausible reference-based object insertion that jointly adapts objects and their surrounding scenes.