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.
Get the few papers worth your time in Computer Vision every morning.
Follow Computer Vision and ReadSearch reads its new papers each day, then brings you the few worth reading, each with its key finding in a sentence.
Newest papers, page 180
OmniCapBench: A Deep-Structured Evaluation Framework for Fine-Grained Audio-Visual Captioning
Multimodal large language models (MLLMs) are rapidly evolving toward continuous audio--visual reasoning, creating an urgent need for evaluations that expose their capability limits.WorldGuide: Goal-Directed Video World Model for Procedural Task Execution
Video generators and video-based world models can synthesize plausible visual trajectories, but long-horizon procedural tasks require generation to adapt to what has actually been produced.OuroWorld: Bringing Any 3D World Alive as Diverse, Endlessly Looping 3D Cinemagraphs
Recent 3D world models generate photorealistic, explorable scenes that remain frozen in time.What 30,000 Hours of Ego-centric Video Does Not Teach
World models offer a promising alternative to physics-based simulators, yet remain far from practical deployment.DreamTrue: Action-Faithful Robot World Model with Counterfactual Post-Training
We present DreamTrue, a multi-view, cross-embodiment robot world model for action-faithful and physically plausible video prediction.Rubric-CEPR: Self-Evolving Image Editing via Reward-Verified Self-Distillation
Instruction-guided image editors have become highly capable, yet improving them further still depends on human-edited training pairs or external reward models.Dex-One2Many: Learning Dexterous Manipulation from a Single Human Demonstration
While learning dexterous manipulation from a single human video offers a promising alternative to costly robot demonstrations, many recent methods predominantly imitate demonstrated motions.Fly-by-Code: Embodied Coding Agents for Aerial Manipulation with Active Visual and Physical Feedback
Embodied coding agents construct robot policies from natural-language instructions by generating executable programs and refining them from execution feedback.CASTER: Formalizing Zero-Shot Manipulation from Synthetic Videos as Constrained Optimization
Prior research on learning from humans often requires real human demonstrations.MIRAGE: Metric Inference and Reliability-Aware Gaussian Estimation from Feed-Forward Vision
Feed-forward 3D priors enable high-quality reconstruction from image streams but often lack reliable metric scale and suffer from long-term trajectory drift.Scaling Multi-Teacher Distillation for Digital Pathology
Multi-teacher distillation allows transferring knowledge from multiple "teacher" networks to a single "student" network.Mind the Temporal Gap: Evaluating Video Models for Temporal Understanding in Driving
Modern video-language models are increasingly treated as general-purpose video reasoners, yet it remains unclear whether they robustly capture temporal dynamics in safety-critical settings such as…MemReg: Streaming Outdoor LiDAR Point Cloud Registration with Hybrid Memory Buffers
Prior outdoor LiDAR registration works are commonly limited by the pair-wise input paradigm, which neglects temporal correlations inherent within streaming sequences.ForcingBooster: Adaptive Patch-wise Denoising for Fast Autoregressive Video Diffusion
Autoregressive video diffusion models have become a leading approach to real-time interactive video generation and video world modeling.Feature Competition and Its Representational Origins in Vision Language Models: Evidence from the Stroop Paradigm
When you ask a vision-language model (VLM) a question with an image, it answers your question based on the image.WoodBR-Cross: A public wood-image dataset and individual-tree-disjoint benchmark for species identification
Wood-image benchmarks can yield optimistic estimates when images from the same tree occur in both training and test sets.Bridging Human and Model Attention: Explainability Analysis of CNN, Mamba, and ViT Architectures with Gaze-Based Validation
High-risk applications of deep learning require precise characterization of model decision-making.Unsupervised Multimodal Reward Modeling
Vision-language reward models are trained on annotated preference pairs, which are expensive to collect, can disagree, and are ranked by benchmark accuracy.Zebra3D: Efficient Hybrid Foundation Models For Scalable 3D Reconstruction
Feed-forward 3D foundation models reconstruct scenes from unposed images, but the quadratic cost of global attention limits their scalability to large view sets.StereoEngine: Scaling Stereo Bimanual Robot Data without Stereo Cameras
Stereo vision is increasingly used for robotic manipulation, with a growing body of work incorporating it into Vision-Language-Action (VLA) models.