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 94
EgoHand: Monocular 3D Hand Reconstruction from Egocentric Video
We introduce EgoHand, a monocular 3D hand reconstruction model that achieves state-of-the-art performance on egocentric video.TerraTransfer++: Demonstration-Free End-to-End Planner
End-to-end autonomous driving has achieved state-of-the-art performance on benchmarks and real-world deployments.Self-Distilling Future Video Representations for World Action Models
World Action Models (WAMs) have emerged as a promising approach to learning generalist robot policies using rich spatiotemporal priors from pre-trained video diffusion models.R4DGS: Referring Segmentation in 4D Gaussian Splatting
Dynamic representations based on 4D Gaussian Splatting (4DGS) have shown strong capabilities in reconstruction and rendering, yet current methods remain limited in supporting complex…MoRE: Motion-Regularized Encoding for Articulated 3D Generation
Generating an articulated object from a single image requires recovering both its appearance and the mechanism governing its parts.Foundation4D: Towards a unified perception and reconstruction model for autonomous vehicles
We introduce Foundation4D, a unified feed-forward model for geometry estimation, 3D detection, semantic occupancy, and Gaussian reconstruction from multi-camera driving video.FiLM-CAM: Keyed Feature Modulation for Conditional-Access Watermarking
We propose FiLM-CAM; a conditional-access image watermarking approach that enforces authorized encoding, decoding, and removal through keyed feature modulation.Latent Space Jam: Layout Guided Video Synthesis
Adding control to video generation often requires training, which demands additional computational resources, data, or architectural changes.VisCurate: Evaluating Behavioral Equivalence of Visual Skills
Modern vision-based agents have shifted toward skill-based problem-solving, where a skill is an executable image-to-image operation, e.g., cropping, thresholding, or edge detection.SplatLab: Autonomous Scientific Discovery for 3DGS Research
Reproducing a published 3DGS paper takes weeks of expert engineering before any extension can be proposed.AVAtt: A Free-Viewing Eye-Tracking Dataset and Benchmark for Visual Attention on Paintings
Saliency and scanpath models are developed almost exclusively on natural photographs, yet paintings are composed by artists to guide the viewer's eye and differ from photographs in texture, colour…Unified Trajectory and 3D Pose Forecasting for Multi-Agent Sports Analysis
Forecasting future human motion requires jointly reasoning about an agent's global trajectory and 3D body pose, which are tightly coupled, particularly in team sports where multiple interacting…VLMProbe: An Open-source Library for VLM Probing and Interpretation
Understanding how vision-language models use visual information requires connecting internal representations to model behavior.AGQ: Action-Guided Ultra-Low-Bit Quantization for Vision-Language-Action Models
Vision-language-action (VLA) models enable robots to perform tasks specified through natural-language instructions, but their large weight footprint challenges deployment on memory-constrained…Diagnosing and Mitigating Evidence Misgrounding in Multimodal Knowledge Editing
Multimodal knowledge editing aims to update visually grounded facts in Multimodal Large Language Models (MLLMs) while preserving unrelated text and visual behaviors.Evaluating Visual Language Models on Visual Grounding for Visually Impaired People
Visual grounding (VG) in visual question answering (VQA) is a fundamental capability of Vision-Language Models (VLMs), enabling the detection of the most relevant region in an image to answer the…Test-time Adaptation for Point Cloud Denoising under Unseen Noise
Although deep learning-based point cloud denoising methods have demonstrated impressive results in recent years, their effectiveness usually degrades substantially in real-world scenarios where the…KPHarness: Co-Evolving Knowledge and Probing for Long-Horizon Gaming Harnesses
A failed gaming trajectory reveals that an agent needs intervention, but not necessarily how its execution harness should change.TokenFlow: Latent Token Rectified Flow Matching for 3D Point Cloud Generation
3D point clouds generation requires capturing both part-level layout and surface detail while preserving permutation equivariance.Using Set Learning to Improve Set-Valued Classifiers on Long-tailed Data
Set-valued classification (SVC) offers a practical approach to communicating uncertainty while maintaining accuracy by predicting variable-sized sets per input rather than fixed-sized sets (e.g…