Every paper checked — nothing hidden

All papers

Every paper checked for brief #4 of 12–19 Oct 2026 — nothing is hidden. Brief papers first.

All17,313 In brief24 More (on-topic)3,333 Not relevant13,754 Not assessed87 Older352 Could not confirm93 Blogs with no paper266 All blogs284

Paper	Topic	Relevance
Appearance Compensation in Volume Rendering The paper theoretically analyzes whether volume rendering with independent sources can reproduce external views while maintaining incorrect internal density. Preprint	Computer vision for industrial applications via arxiv · 15 Oct, 06:18	Not relevant Theoretical volume rendering physics, not industrial visual quality control.
What Really Works for Universal Multimodal Embeddings? A Controlled Study of Contrastive Training Strategies The paper conducts a controlled benchmark study evaluating common contrastive training strategies for universal multimodal embedding learning. Preprint	Computer vision for industrial applications via arxiv · 15 Oct, 06:18	Not relevant Evaluates multimodal representation learning, not industrial inspection.
Use Of Convolutional Neural Networks In Detection Of Branch Dieback Disease In Pequi Trees The paper compares five convolutional neural network architectures for detecting branch dieback disease in pequi tree images. Preprint	Multimodal models via arxiv · 15 Oct, 06:18	Not relevant Focuses on unimodal computer vision for plant disease diagnosis.
Use Of Convolutional Neural Networks In Detection Of Branch Dieback Disease In Pequi Trees The paper compares five convolutional neural network architectures for detecting branch dieback disease in pequi tree images. Preprint	Computer vision for industrial applications via arxiv · 15 Oct, 06:18	Not relevant Focuses on agricultural tree disease detection, not industrial manufacturing.
Global Disaster Risk Assessment Using World Risk Index Data: A Geospatial and Visual Analytics Approach The paper analyzes historical World Risk Index data using Python visual analytics libraries to assess global natural disaster vulnerabilities. Preprint	Computer vision for industrial applications via arxiv · 15 Oct, 06:18	Not relevant Focuses on global disaster risk analytics, not industrial inspection.
Global Disaster Risk Assessment Using World Risk Index Data: A Geospatial and Visual Analytics Approach The paper analyzes historical World Risk Index data using Python visual analytics libraries to assess global natural disaster vulnerabilities. Preprint	Multimodal models via arxiv · 15 Oct, 06:18	Not relevant Geospatial data visualization, not multimodal vision-language models.
BrainAid: Efficient Brain Tumor Detection Using Lightweight CNNs and Explainable AI for Resource-Constrained Environments The paper evaluates lightweight convolutional networks and vision transformers for multi-class brain tumor classification from MRI scans. Preprint	Multimodal models via arxiv · 15 Oct, 06:18	Not relevant Focuses on unimodal vision classification for medical imaging.
BrainAid: Efficient Brain Tumor Detection Using Lightweight CNNs and Explainable AI for Resource-Constrained Environments The paper evaluates lightweight convolutional networks and vision transformers for multi-class brain tumor classification from MRI scans. Preprint	Computer vision for industrial applications via arxiv · 15 Oct, 06:18	Not relevant Addresses medical MRI tumor detection, not industrial quality control.
Region Aware Squeeze-and-Excitation Networks for Image Segmentation The paper introduces spatially guided pooling modules to enable region-aware channel recalibration in convolutional networks for image segmentation. Preprint	Computer vision for industrial applications via arxiv · 15 Oct, 06:18	Not relevant General computer vision segmentation architecture, not industrial defect detection.
Region Aware Squeeze-and-Excitation Networks for Image Segmentation The paper introduces spatially guided pooling modules to enable region-aware channel recalibration in convolutional networks for image segmentation. Preprint	Multimodal models via arxiv · 15 Oct, 06:18	Not relevant Focuses purely on vision segmentation modules, not multimodal data.
TIDE: Trajectory-Informed Skill Distillation for Efficient Text-to-Video Prompt Optimization The paper introduces a framework that distills iterative prompt search into rule modules for efficient text-to-video generation. Preprint	Computer vision for industrial applications via arxiv · 15 Oct, 06:18	Not relevant Deals with text-to-video generation, not industrial visual inspection.
Generative Quantum Machine Learning Methods for Cancer Detection using Augmented Datasets The paper proposes a generative quantum machine learning method to create synthetic breast ultrasound images for training cancer detection models. Preprint	Multimodal models via arxiv · 15 Oct, 06:18	Not relevant Focuses on medical image classification and quantum ML, not multimodal systems.
Generative Quantum Machine Learning Methods for Cancer Detection using Augmented Datasets The paper proposes a generative quantum machine learning method to create synthetic breast ultrasound images for training cancer detection models. Preprint	Computer vision for industrial applications via arxiv · 15 Oct, 06:18	Not relevant Focuses on medical cancer detection, not industrial manufacturing inspection.
Drive3R: Block-wise Streaming Geometric Foundation Models for Autonomous Driving The paper presents a block-wise streaming geometric foundation model for continuous 3D reconstruction and simulation in autonomous driving. Preprint	Multimodal models via arxiv · 15 Oct, 06:18	Not relevant Focuses on 3D geometric reconstruction for driving, not cross-modal models.
Drive3R: Block-wise Streaming Geometric Foundation Models for Autonomous Driving The paper presents a block-wise streaming geometric foundation model for continuous 3D reconstruction and simulation in autonomous driving. Preprint	Computer vision for industrial applications via arxiv · 15 Oct, 06:18	Not relevant Autonomous driving reconstruction is explicitly excluded from this topic's scope.
RootSLAM: Square Root Bundle Adjustment for Visual-Inertial SLAM The paper introduces a visual-inertial SLAM system that applies square-root bundle adjustment to achieve faster multi-camera tracking on low-power devices. Preprint	Multimodal models via arxiv · 15 Oct, 06:18	Not relevant Addresses geometric visual-inertial SLAM, not multimodal language-vision foundation models.
RootSLAM: Square Root Bundle Adjustment for Visual-Inertial SLAM The paper introduces a visual-inertial SLAM system that applies square-root bundle adjustment to achieve faster multi-camera tracking on low-power devices. Preprint	Computer vision for industrial applications via arxiv · 15 Oct, 06:18	Not relevant Covers SLAM for robotics, not industrial defect detection or inspection.
TRIG: Toward Measuring Texture Realism in Image Generation The paper proposes an evaluation metric using a texture-trained GAN discriminator backbone to measure texture realism in generated images. Preprint	Computer vision for industrial applications via arxiv · 15 Oct, 06:18	Not relevant Evaluates generative image realism, not manufacturing defect detection or inspection.
TRIG: Toward Measuring Texture Realism in Image Generation The paper proposes an evaluation metric using a texture-trained GAN discriminator backbone to measure texture realism in generated images. Preprint	Multimodal models via arxiv · 15 Oct, 06:18	Not relevant Focuses on computer vision texture metrics, not multimodal integration.
ExeWorldBench: Benchmarking Code-Based Executable 3D World Modeling The paper introduces a benchmark evaluating whether coding agents can construct interactive, code-based 3D simulations that capture underlying physical principles. Preprint	Computer vision for industrial applications via arxiv · 15 Oct, 06:18	Not relevant Focuses on code-based 3D world modeling, not industrial quality control.
Automated carotid artery atherosclerotic inflammation segmentation in PET using MSR-Net The paper presents a two-stage multiscale residual convolutional network to segment and quantify carotid artery atherosclerotic inflammation on PET images. Preprint	Multimodal models via arxiv · 15 Oct, 06:18	Not relevant Specialized medical image segmentation rather than general multimodal language-vision models.
Automated carotid artery atherosclerotic inflammation segmentation in PET using MSR-Net The paper presents a two-stage multiscale residual convolutional network to segment and quantify carotid artery atherosclerotic inflammation on PET images. Preprint	Computer vision for industrial applications via arxiv · 15 Oct, 06:18	Not relevant Medical PET/MR imaging, not industrial defect detection.
ASM-6D: Fast Certified Pose-Shape Inference with Complete Correspondence Flow Maps The paper introduces an efficient method that couples generative complete-geometry prediction with active shape models for category-level 6D pose estimation. Preprint	Multimodal models via arxiv · 15 Oct, 06:18	Not relevant RGB-D 3D pose estimation without multimodal language-vision capabilities.
ASM-6D: Fast Certified Pose-Shape Inference with Complete Correspondence Flow Maps The paper introduces an efficient method that couples generative complete-geometry prediction with active shape models for category-level 6D pose estimation. Preprint	Computer vision for industrial applications via arxiv · 15 Oct, 06:18	Not relevant Studies robotic grasping and 6D pose estimation, not production line inspection.
Channel Match: Calibrating Shape Latents for Few-Step 3D Generation The paper proposes a few-step distillation framework for native 3D generation to mitigate sampling-induced latent drift that damages texture synthesis. Preprint	Computer vision for industrial applications via arxiv · 15 Oct, 06:18	Not relevant Deals with 3D generative asset modeling, not manufacturing inspection.
Channel Match: Calibrating Shape Latents for Few-Step 3D Generation The paper proposes a few-step distillation framework for native 3D generation to mitigate sampling-induced latent drift that damages texture synthesis. Preprint	Multimodal models via arxiv · 15 Oct, 06:18	Not relevant Focuses on 3D latent distillation without multimodal reasoning or language integration.
TempoKV: Predictive KV Cache Quantization for Autoregressive Video Generation The paper presents a predictive KV cache quantization method exploiting temporal predictability to reduce memory overhead in autoregressive video generation models. Preprint	Computer vision for industrial applications via arxiv · 15 Oct, 06:18	Not relevant Video diffusion cache quantization, not industrial anomaly detection.
CIViC: Evidence Gates for Audio-Conditioned Visual Prediction on Proxy Tasks The paper presents a four-gate verification protocol to evaluate whether audio-conditioned visual prediction models genuinely rely on input audio signals. Preprint	Computer vision for industrial applications via arxiv · 15 Oct, 06:18	Not relevant Evaluates audio-visual prediction checks, not industrial defect detection.
CIViC: Evidence Gates for Audio-Conditioned Visual Prediction on Proxy Tasks The paper presents a four-gate verification protocol to evaluate whether audio-conditioned visual prediction models genuinely rely on input audio signals. Preprint	AI safety and reliability in deployment via arxiv · 15 Oct, 06:18	Not relevant Analyzes feature attribution in audio-visual tasks, not LLM safety guardrails.
CIViC: Evidence Gates for Audio-Conditioned Visual Prediction on Proxy Tasks The paper presents a four-gate verification protocol to evaluate whether audio-conditioned visual prediction models genuinely rely on input audio signals. Preprint	LLM evaluation and benchmarks via arxiv · 15 Oct, 06:18	Not relevant Tests audio-conditioned vision proxy tasks, not LLM evaluation or benchmarks.
CIViC: Evidence Gates for Audio-Conditioned Visual Prediction on Proxy Tasks The paper presents a four-gate verification protocol to evaluate whether audio-conditioned visual prediction models genuinely rely on input audio signals. Preprint	Small and efficient models via arxiv · 15 Oct, 06:18	Not relevant Addresses audio-visual feature gating, not model compression or efficient serving.
BaT-SAM: Introducing Inductive Bias into SAM via a Mixture of Convolutional Experts for Brain Tumor Segmentation The paper adapts the Segment Anything Model for automated brain tumor segmentation using multi-scale convolutional experts without requiring manual inference prompts. Preprint	Multimodal models via arxiv · 15 Oct, 06:18	Not relevant Vision-only medical image segmentation without multimodal text-image reasoning.
BaT-SAM: Introducing Inductive Bias into SAM via a Mixture of Convolutional Experts for Brain Tumor Segmentation The paper adapts the Segment Anything Model for automated brain tumor segmentation using multi-scale convolutional experts without requiring manual inference prompts. Preprint	Computer vision for industrial applications via arxiv · 15 Oct, 06:18	Not relevant Medical MRI segmentation, not industrial defect detection.
Video-Based Sexual Harassment Detection Using Fine-Tuned Video Transformers The paper evaluates fine-tuned video transformers on an expanded video dataset to detect instances of sexual harassment for surveillance applications. Preprint	Multimodal models via arxiv · 15 Oct, 06:18	Not relevant Standard video classification without cross-modal interaction or multimodal foundation models.
Video-Based Sexual Harassment Detection Using Fine-Tuned Video Transformers The paper evaluates fine-tuned video transformers on an expanded video dataset to detect instances of sexual harassment for surveillance applications. Preprint	Computer vision for industrial applications via arxiv · 15 Oct, 06:18	Not relevant Focuses on surveillance harassment detection, not industrial defect detection.
UniForge3D: Joint 3D Reconstruction and Generation in a Shared Anchor-Guided Space The paper introduces a method that unifies 3D reconstruction and generation within a shared anchor-guided coordinate space to preserve observed geometry. Preprint	Computer vision for industrial applications via arxiv · 15 Oct, 06:18	Not relevant Focuses on 3D asset generation, not manufacturing defect detection.
UniForge3D: Joint 3D Reconstruction and Generation in a Shared Anchor-Guided Space The paper introduces a method that unifies 3D reconstruction and generation within a shared anchor-guided coordinate space to preserve observed geometry. Preprint	Multimodal models via arxiv · 15 Oct, 06:18	Not relevant Standard 3D computer vision reconstruction without multimodal language integration.
VideoEvoHarness: Self Evolving Agent Harness from Unlabeled Videos for Video Understanding The paper proposes an agent harness that autonomously evolves questioner and solver workflows from unlabeled video data without updating base model parameters. Preprint	Computer vision for industrial applications via arxiv · 15 Oct, 06:18	Not relevant Focuses on video reasoning agents, not industrial production inspection.
OmniRSI: Taming Latent Diffusion for Unified Multimodal Remote Sensing Image Generation The paper proposes a unified latent diffusion architecture with a custom variational autoencoder for multimodal remote sensing image generation. Preprint	Computer vision for industrial applications via arxiv · 15 Oct, 06:18	Not relevant Remote sensing imagery, which is explicitly excluded from topic focus.
Harnessing SPAD Noise: Test-Time Gated Attention for Indoor Depth Estimation The paper introduces a lightweight test-time attention framework that leverages single-photon sensor noise as an informative prior for indoor depth estimation. Preprint	AI safety and reliability in deployment via arxiv · 15 Oct, 06:18	Not relevant Studies sensor-based depth estimation, not deployment AI safety or guardrails.
Harnessing SPAD Noise: Test-Time Gated Attention for Indoor Depth Estimation The paper introduces a lightweight test-time attention framework that leverages single-photon sensor noise as an informative prior for indoor depth estimation. Preprint	Computer vision for industrial applications via arxiv · 15 Oct, 06:18	Not relevant Indoor depth estimation, not industrial inspection or manufacturing lines.
Harnessing SPAD Noise: Test-Time Gated Attention for Indoor Depth Estimation The paper introduces a lightweight test-time attention framework that leverages single-photon sensor noise as an informative prior for indoor depth estimation. Preprint	Multimodal models via arxiv · 15 Oct, 06:18	Not relevant Focuses on sensor noise for depth prediction, not vision-language multimodal models.
Harnessing SPAD Noise: Test-Time Gated Attention for Indoor Depth Estimation The paper introduces a lightweight test-time attention framework that leverages single-photon sensor noise as an informative prior for indoor depth estimation. Preprint	LLM evaluation and benchmarks via arxiv · 15 Oct, 06:18	Not relevant Proposes a depth estimation method, not LLM evaluation benchmarks.
Harnessing SPAD Noise: Test-Time Gated Attention for Indoor Depth Estimation The paper introduces a lightweight test-time attention framework that leverages single-photon sensor noise as an informative prior for indoor depth estimation. Preprint	Small and efficient models via arxiv · 15 Oct, 06:18	Not relevant Focuses on sensor depth estimation, not small language model compression.
Rethinking Supervision in Document Unwarping: A Self-consistent Flow-free Approach The paper introduces a flow-free deep network for smartphone document image unwarping using geometric consistency and undistorted document supervision. Peer-reviewed	Computer vision for industrial applications via arxiv · 15 Oct, 06:18	Not relevant Focuses on smartphone document unwarping, not factory quality control.
EmoTrace-Bench: Diagnosing Emotional Expression in Text-to-Video Generation through Controlled Cues and Intensity The paper introduces a benchmark to evaluate text-to-video models across controlled emotional expression levels and specific audiovisual affective cues. Preprint	Computer vision for industrial applications via arxiv · 15 Oct, 06:18	Not relevant Benchmark for text-to-video emotion generation, not industrial visual inspection.
Semantic Saliency from Multi-Modal Large Language Model Scene Understanding Maps The paper develops an automated method that measures semantic saliency by evaluating how removing individual objects alters multimodal model scene descriptions. Preprint	Computer vision for industrial applications via arxiv · 15 Oct, 06:18	Not relevant Studies semantic saliency modeling, not factory defect inspection.
Structured Stateful Relational Scripts with a High-Quality Dataset for Multi-Shot Audio-Visual Video Generation The paper introduces structured stateful relational scripts and a paired dataset to coordinate persistent identities and audio events in multi-shot video generation. Preprint	Computer vision for industrial applications via arxiv · 15 Oct, 06:18	Not relevant Focuses on video generation, not manufacturing or inspection.
Semantically Steerable Image Tokenization The paper proposes an adaptive image tokenizer that balances pixel reconstruction and semantic features to prevent discarding critical semantic content during compression. Preprint	Computer vision for industrial applications via arxiv · 15 Oct, 06:18	Not relevant Deals with image tokenization compression, not industrial defect detection.
GNFormer: Gaussian Neural Field Transformer for Efficient Camera-based Occupancy Prediction The paper introduces a 3D Gaussian neural field transformer for efficient, camera-based occupancy prediction in robotic perception systems. Preprint	Multimodal models via arxiv · 15 Oct, 06:18	Not relevant Focuses on 3D occupancy prediction without cross-modal language or multimodal reasoning.
GNFormer: Gaussian Neural Field Transformer for Efficient Camera-based Occupancy Prediction The paper introduces a 3D Gaussian neural field transformer for efficient, camera-based occupancy prediction in robotic perception systems. Preprint	Computer vision for industrial applications via arxiv · 15 Oct, 06:18	Not relevant Occupancy prediction for autonomous vehicles and UAVs, not manufacturing lines.
UMAS3D: Unified Mask-Free 3D Editing with Region-Adaptive Source Preservation The paper proposes a training-free 3D editing framework that estimates edit regions without masks to preserve unedited source geometry and appearance. Preprint	Computer vision for industrial applications via arxiv · 15 Oct, 06:18	Not relevant Focuses on 3D asset editing, not industrial visual inspection.
A Plausible Future Is Not a Causal Future: Can Video Models Generate How the World Unfolds? The paper presents a simulator-grounded benchmark to evaluate whether image-to-video generation models capture causal physical cascades and counterfactual dynamics faithfully. Preprint	Computer vision for industrial applications via arxiv · 15 Oct, 06:18	Not relevant Evaluates video world models, not industrial defect detection or manufacturing.
Genesis: Visual Augmentation Primitives for Multimodal Chain-of-Thought Reasoning The paper introduces an image augmentation pipeline that generates diverse visual variants to anchor multimodal chain-of-thought reasoning in visual evidence. Preprint	Computer vision for industrial applications via arxiv · 15 Oct, 06:18	Not relevant Focuses on multimodal visual reasoning benchmarks, not industrial visual inspection.
Truncation Samplers Are Nested: Comparing Decoding Rules Is a Measurement Problem The paper presents a theoretical framework using nesting properties to calculate distance bounds and compare language model truncation sampling algorithms efficiently. Preprint	Computer vision for industrial applications via arxiv · 15 Oct, 06:18	Not relevant Studies language model sampling theory, not industrial computer vision.
Truncation Samplers Are Nested: Comparing Decoding Rules Is a Measurement Problem The paper presents a theoretical framework using nesting properties to calculate distance bounds and compare language model truncation sampling algorithms efficiently. Preprint	AI safety and reliability in deployment via arxiv · 15 Oct, 06:18	Not relevant Focuses on sampling divergence measurement rather than AI safety or guardrails.
Truncation Samplers Are Nested: Comparing Decoding Rules Is a Measurement Problem The paper presents a theoretical framework using nesting properties to calculate distance bounds and compare language model truncation sampling algorithms efficiently. Preprint	Multimodal models via arxiv · 15 Oct, 06:18	Not relevant Analyzes text generation decoding rules, not multimodal models.
Ellipsoids from Tangents The paper introduces an algorithm that fits multiple ellipsoids in multi-dimensional data by leveraging tangent equations rather than raw points alone. Preprint	Multimodal models via arxiv · 15 Oct, 06:18	Not relevant Focuses on mathematical ellipsoid fitting from tangents, not multimodal AI.
Ellipsoids from Tangents The paper introduces an algorithm that fits multiple ellipsoids in multi-dimensional data by leveraging tangent equations rather than raw points alone. Preprint	Computer vision for industrial applications via arxiv · 15 Oct, 06:18	Not relevant Presents a geometric algorithm for fitting ellipsoids, not industrial visual inspection.
FireNav: Decision-Oriented Reconstruction Evidence Routing for Vision-Language Navigation in Indoor Fire Environments The paper presents a framework aligning visual image restoration with navigation decisions for vision-language navigation in degraded indoor fire environments. Preprint	Computer vision for industrial applications via arxiv · 15 Oct, 06:18	Not relevant Addresses indoor fire navigation for robots, not industrial defect inspection.

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