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 91
BlazeVGGT: 13x Faster VGGT at 2,000 Frames via Camera Token without Training
Feed-forward visual geometry models, exemplified by VGGT, have demonstrated strong multi-view reconstruction capabilities through dense global attention.Extending Affordance Segmentation for Wearable Robots to Multi-Object Images
This paper proposes a refinement to existing vision-based portable pipelines for the recognition of graspable object parts.Balancing Foundation Models and Trait-Specific Learning for Forehead-Crease Recognition
Biometric recognition often degrades under partial facial vis- ibility, where conventional facial cues are occluded.AutoPhyX: Automatic Text-Condition Physics Property Generation
High-fidelity 4D physical simulation requires accurate physical parameter assignments that align with diverse material properties.Supervision-Adaptive Curriculum and Guarded Anti-Curriculum Learning for Dense Prediction
Curriculum learning orders samples by difficulty, but difficulty alone does not establish supervision reliability for dense prediction.Melange: A Synthetic Visual Bias Benchmark for Multi-modal Large Language Models
Multi-modal Large Language Models (MLLMs) have seen broad adoption, but their biases are still far less examined than those of standard LLMs, creating possible social harms when deployed in…Hyperspherical Simplex Representations for Backward-Compatible Retrieval
Training modern AI models has become increasingly expensive, and updating deployed models can alter their internal feature representations, affecting applications built upon them.Generalized CycleGRPO for Fine-Grained Multimodal Understanding and Grounding
Fine-grained multimodal intelligence requires models to both understand a designated region and localize it from language.Rethinking Underwater Image Enhancement: Learning through Text-Guided Degradation Curriculum
Existing paired clean-degraded datasets have advanced learning-based underwater image enhancement, but they remain either limited in scale or difficult to acquire, and still fail to adequately cover…Unlocking Spatial Grounding in Flow-Matching Models via SNR Tuning
Despite the success of foundation models in image synthesis, achieving fine-grained spatial control remains a significant challenge, typically requiring auxiliary structural adapters or complex…CineEvolve: An Agentic Self-Evolution Framework for Cinematic Multi-Shot Video Generation
Cinematic multi-shot video generation requires both narrative planning and iterative refinement.No Frames, Just Frequencies: Bandwidth-Efficient Deployment-Time Adaptation for Smart Glasses
Deep neural networks deployed on smart glasses must adapt to changes in the distribution of incoming data while adhering to strict privacy and device constraints.Diff-IrisPAD: Modeling Bona Fide Iris Distributions for Unsupervised Presentation Attack Detection
Iris recognition systems are vulnerable to presentation attacks (PAs), including textured contact lenses, print replays, and synthetic irises.An interpretable deep learning method for early hepatocellular carcinoma diagnosis on multiphase CT
Early diagnosis of hepatocellular carcinoma is critical to preserve access to curative treatment options.TernScope: Model-Hardware Co-Design for Efficient Ternary Endoscopic Segmentation
Edge medical segmentation must reconcile small model size, high accuracy, and fast inference.FogTTA: Online Test-Time Adaptation for Robust Transformer-based Object Detection in Foggy Weather
Object detection models for autonomous driving commonly experience substantial performance drops when deployed under adverse weather due to the domain shift between training data and real-world…OpenEarth-OVS44: A Multimodal Remote Sensing Dataset for Open-Vocabulary Segmentation
In remote sensing, open-vocabulary segmentation is particularly important for flexible and scalable land-cover understanding across diverse regions, as it improves generalization to novel categories…Joint Semantic-Channel Coding and Modulation for Generative Image Transmission
Digital image transmission typically optimizes source coding, channel coding, and modulation separately, limiting how source representations adapt to channel impairments.Reading the Room: Scale-ambiguous Semantic Registration of Sparse VSLAM Maps to Floor Plans in Partially Built Environments
Many robotic construction applications, such as progress tracking, require registering a sensor trajectory to a prior 2D floor plan.MS2CAST: A Video Anomaly Detection Framework via Multi-Scale Spatial Cross-Attention and Efficient Spatiotemporal Networks
Video anomaly detection (VAD) is a challenging task for surveillance systems due to the scarcity and diversity of anomalous events.