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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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Newest papers, page 229
MEMO: Multi-Level Entity-Aware Memory for Streaming Video Understanding
Streaming video understanding requires models to process unbounded visual streams while preserving rich visual semantics across vast temporal horizons, posing a fundamental challenge for memory…FLOW: Feature-Level Optimal Warping for Generalized Remote Physiological Measurement
Remote photoplethysmography (rPPG) enables non-contact physiological measurement but remains vulnerable to domain shifts from illumination, motion, and sensors.From Image Interpretation to Clinical Reasoning: Upstream Physician-Context-Aware Multimodal Learning with Causal Reinforcement Learning
Major adverse cardiovascular events (MACE) remain the leading cause of mortality worldwide.World-as-Graph: Relational World Modeling Through Latent Space Graphs
World models aim to learn representations of real-world environments and predict their future evolution.On the Relaxation of Conditional Independence Assumption for Image Segmentation
In semantic segmentation, a recent line of RankSEG methods directly optimizes Dice/IoU scores at inference time, improving alignment with evaluation metrics without modifying model training.Beyond Spatial-Domain Supervision: A Relation Constrained Space for Multi-Modal Image Fusion
Multi-modal image fusion (MMIF) aims to form a single image by integrating shared information, preserving complementary cues, and coordinating cross-modal conflicts across modalities.PARK: Accurate Block Retrieval for Sparse Attention in Video Diffusion Transformers
Diffusion Transformers (DiTs) have become a dominant architecture for video generation, but their efficiency is limited by the quadratic complexity of full attention.Mitigating Object Hallucination in Large Vision-Language Models via False Discovery Controlled Visual Data Splitting
Multiple object hallucination, where large vision-language models (LVLMs) generate objects not supported by the visual input, is a persistent challenge caused by visual uncertainty during decoding.MeshOctave generates meshes via cascading resolution transitions
Generating compact, artist-style meshes with explicit topology typically relies on autoregressive models which incur prohibitive sequential per-token costs, or continuous flow models that depend on…Anchoring Adversarial Trajectories to Data Manifolds: A Bilevel Transfer Optimization Framework
A key bottleneck in adversarial transfer is a trajectory-level geometric disconnect: ambient gradients often drift away from the intrinsic data manifold, causing surrogate-specific overfitting.When Integral Meets Decomposition: A Signal-Level Self-Supervised Feature Decompose Paradigm for Multi-Modal Image Fusion
Multimodal image fusion (MMIF) aims to integrate complementary information from different modalities into a high-quality fused image and support downstream tasks.Frame Differential On-Policy Self-Distillation for Video Reasoning
Reinforcement learning (RL) has substantially improved the reasoning ability of multimodal language models through verifiable rewards and increasingly fine-grainedvisual or temporal credit assignment.Persistent Watermarking of Text-to-Image Models
Text-to-image (T2I) generation is gaining increasing popularity with the general public, motivating the development of reliable mechanisms for copyrighting such models given their expensive training…TED:Text-Axis Evidence Decomposition for Prompted Anomaly Localization
CLIP is a powerful vision-language model, but it was not designed for fine-grained defect localization; CLIP-based anomaly detectors therefore adapt it with prompts or lightweight modules to…BadAction: Backdoor Attacks on Interactive Video Generation via Action-Guided Triggers
Interactive video generation (IVG) models have achieved remarkable progress in producing controllable visual content guided by user-defined actions, yet their security vulnerabilities remain largely…TSMD: Temporal-Stream Modality Dropout for Robust Video Highlight Detection
Existing multimodal video highlight detectors typically assume that visual, audio, and textual streams are continuously available.Agentic Tool-Augmented Reasoning for Explainable Image Forgery Detection
Conventional image forgery detection methods produce binary scores or pixel-level masks without interpretable evidence, while recent multimodal large language model (MLLM)-based approaches generate…MRI Super-Resolution with RCDM/WaveMix and Task-Aware Segmentation
Super-resolution and quality enhancement of 1.5\,T brain MRI are normally validated with image-fidelity metrics, although their purpose is to improve downstream analysis.UGOD: Uncertainty-Guided Opacity and Dropout for Sparse-View 3D Gaussian Splatting
Sparse-view 3D Gaussian Splatting is prone to overfitting because limited observations leave many Gaussian primitives weakly constrained, yet their contributions are still accumulated through alpha…DeCoPrune: Efficient KV-Cache Pruning for Autoregressive Video Diffusion via Denoising Consistency
Autoregressive video diffusion supports streaming generation and interactive control, but its KV cache grows with the generated history.