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 20
Low-Density 3D Point Cloud Classification
3D point cloud classification, a task in computer vision, has recently gained substantial interest due to its extensive applications across various domains such as augmented and virtual reality…Wonder 4: A Mixture-of-Experts Recipe for Image Quality Enhancement
A real photograph is often blurry, grainy, compressed, scratched, and low-resolution at the same time.OpenBrain: An Auditable Generated-Label Release for Whole-Brain MRI Parcellation
Automatic tools can now generate whole-brain MRI parcellations at cohort scale, but generated-label releases often provide little evidence about which cases are reliable enough to reuse.GSCV++: Lightweight 3D Gaussian Splatting Sequence Compression via Standard Video Codecs
This paper presents GSCV++, a lightweight pipeline for 3D {G}aussian {S}platting (GS) sequences {C}ompression with standard {V}ideo codecs.Visibility-Aware Reference Generation for Benchmarking Visual 3D Reconstruction in Vegetation-Rich Environments
Reliable evaluation of visual 3D reconstruction and depth estimation in vegetation-rich outdoor environments is limited by the scarcity of geometric ground-truth data and the cost of complete…DreamX: Video Diffusion Model is a Universal Latent Action Learner
Learning a universal action representation from video requires modeling dynamics that are consistent across different executions of the same action yet invariant to changes in embodiment and…SurgTransfer: Multi-Step Latent Action Modeling for Action Transfer in Surgical World Model
Surgical world models have the potential to provide intra-operative guidance, accelerate risk-free training and facilitate transfer of expert surgical maneuvers.SO(3)-Equivariant Learning on CAD Boundary Representations
Learning on boundary representations (B-reps) requires robustness to the pose of a part, since CAD models are not stored in a canonical orientation.From Tokens to Trajectories: Parameter-Efficient Continuous Adaptation of Unified Multimodal Models
While discrete tokenization in Unified Multimodal Models (UMMs) establishes strong semantic reasoning, it introduces a strict quantization bottleneck that degrades fine-grained visual details, often…From Activation to Intervention: Interpreting Sparse Visual Features through Reconstruction
Sparse autoencoders (SAEs) decompose visual representations into individual features, offering a promising basis for explaining model behavior.Rewrite, Then Veto: Rewriter-Agnostic Edit Gating for LLM-Based Post-OCR Correction
LLMs can repair noisy OCR transcripts of historical documents, but they also change text that was already correct.How Finely Can Vision-Language Models See Biology? Bio-VQA: A Benchmark for Taxonomic, Morphological, Spatial and Individual Reasoning
In biodiversity monitoring, a single image raises several questions: which taxon, how many, which trait, and whether the individual has been seen before.Lesion Overlap Ranks PET Segmentation Models but Does Not Certify Patient-Level Tumor Burden
Metabolic tumor volume (MTV) summarizes whole-body PET disease burden for prognostic stratification and treatment assessment.Discarded or Unreachable? Diagnosing and Repairing Spatial Relation Failure in Vision--Language Similarity
Contrastive vision-language models score left/right relations near chance, but the symptom has two causes that call for opposite repairs: the relation may survive in the pooled embedding yet be…Role-based Effectiveness of an Epistemic Uncertainty Estimate in Training Models for Semantic Segmentation of 3D LiDAR Point Clouds
Point cloud segmentation is a fundamental task in 3D data analysis, with applications across robotics, augmented and virtual reality, and remote sensing.ChangeJEPA: Predict Before You Compare for Remote Sensing Change Detection
Remote sensing change detection is typically formulated as Siamese feature comparison, where two images are encoded independently and a decoder determines which discrepancies correspond to…Whose Values Are Generated? Measuring Visual Value Leakage in Multilingual Text-to-Image Generation
Text-to-image (T2I) systems serve users across languages and cultural contexts.Multimodal Fusion Methods for Whole-Slide Images and Clinical Data in Inflammatory Bowel Disease
Multimodal AI fusion of histology and clinical data is an active research area in computational pathology, but fusion methods are rarely compared under identical conditions and across different…BrainBind: Bridging Synchronized EEG and fMRI through Long-Form Naturalistic Video Representations
Real-world vision is dynamic and scene-rich, while EEG and fMRI resolve it at complementary temporal and spatial scales.GaussianRenderFormer: Transformer-based Rendering of 3D Gaussian Splats
Can a neural network learn to render 3D Gaussian splats on its own, with no rasterizer in the renderer?