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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: 4,996 arXiv preprints and 4 OpenAlex records.
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Efficient Test-time Adaptation through Candidate Verification and Divergence Shifts
Vision-language models (VLMs) achieve strong zero-shot transferability but remain vulnerable to target-domain shifts at inference time.Bayesian Optimization in Sequence-to-Architecture Latent Space for Zero-Shot NAS
Zero-shot Neural Architecture Search removes the prohibitive cost of traditional NAS, but its search process is typically based on the evolutionary algorithm (EA); lacking an explicit model of the…Loss-Invariant Projections as Passive Probes of Learned Representations
Learned feature representations in neural networks often contain structure beyond that directly used by the final task output.EORestore-Agent: Fidelity-Guided Agentic Restoration of Remote Sensing Images with Composite Degradations
Remote sensing images often carry composite degradations, in which haze, cloud, noise, blur, low light, and low resolution coexist.MoCAR: Motion-code Coordinate-aware AutoRegression for Continuous Trajectory Forecasting
Autoregressive generation is natural for language, where predicted tokens can be directly reused as the next prediction state, but trajectory forecasting lacks such a clean token: motion is…Frequency-Decoupled Diffusion Guidance for Non-Blind Image Deblurring
Pretrained diffusion models provide powerful image priors for training-free posterior sampling in image restoration.LeAVJEPA: A Minimalist Architecture for Audio-Visual Self-Supervised Learning
Prior audio-visual self-supervised learning methods rely on mechanisms such as EMA target encoders, prediction heads, reconstruction decoders, and contrastive losses.Joint Class-Time Learning for Video Classification with Multi-Instance Partial-Label Learning
Multi-instance partial-label learning (MIPL) addresses inexact supervision in both the instance and label spaces, which can be applied to video classification.CentriQ: Calibration-Free Quantization of Diffusion Transformers via Exact Mean Centering
Diffusion transformers (DiTs) achieve state-of-the-art image generation, but their sampling cost limits deployment.VepAgent: Bridging Causal-Transition via Tool-Augmented Reinforcement Learning for Video Event Prediction
Multimodal Large Language Models (MLLMs) have demonstrated remarkable potential in video understanding, yet their reliance on retrospective summarization and text-centric priors often limits their…Wiring Matters: Injection Topology and Initialization of Affordance Heads in Vision-Language-Action Policies
Dense affordance supervision is an appealing auxiliary signal for vision-language-action (VLA) policies, yet naively co-training an affordance head can severely damage instruction following.Readout Blindness: VLM Scores Miss the Spatial Direction Their Frozen Encoders Retain
CLIP-like vision-language models remain a cornerstone of multimodal systems, yet their scores stay near chance on directed spatial relations, such as whether one object is left of another.Dual Variational Autoencoders for Efficient Sim-to-Real Transfer in Low-Cost Robotic Navigation
Vision-based autonomous navigation for low-cost robots remains a fundamental challenge, primarily due to the significant gap between simulated training environments and real-world operational…SPIN: Image Immunization Against Diffusion Editing via Single-Step Projection in Stochastic Neighborhoods
Diffusion models have greatly advanced instruction-guided image editing, while also raising concerns about unauthorized image manipulation.BabelFake: A Multilingual Audio-Visual DeepFake Benchmark
Reliable and practical audio-visual DeepFake detection requires benchmarks that reflect diverse linguistic contexts and modern data synthesis pipelines for visual as well as audio manipulations.MeSD: Multi-Evidence Self-Distillation for VideoLLM
While reinforcement learning with verifiable rewards provides reliable outcome supervision for VideoLLMs, sequence-level rewards offer limited token-level guidance.KineWorld: Action-Induced Transport Fields for Embodied World Modeling
Embodied world models predict the visual consequences of candidate actions before execution.Environmental sensor readings in two crop disease image datasets identify the session in which each image was taken
Integrating environmental sensor data with leaf imagery is widely reported to boost crop disease classification accuracy.MTOR: Generalizable AI-Generated Video Detection with Multimodal Semantics and Temporal Over-Regularity
The rapid evolution of video generation has narrowed the perceptual gap between authentic and synthetic videos, making generalizable AI-generated video detection increasingly challenging.Multi-Task Partially Supervised Learning for Super-Resolution and Semantic Segmentation on Earth Observation data
Super-resolution and semantic segmentation are known to benefit one another, especially in the Earth observation context.