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 129
FutureLift: Lifting Trajectory Proposals into Bidirectional Future Graphs for Motion Forecasting
Accurate motion prediction is critical for safe autonomous driving, yet even strong forecasters leave residual errors in their multimodal proposals.Skill-Decoupled On-Policy Expert Distillation for Unified Vision-Language Models
Reinforcement learning (RL) can elicit specialized visual capabilities in vision-language models (VLMs), yet jointly optimizing heterogeneous objectives often introduces cross-capability gradient…How Much Physics Can Vision Learn from Audio? Probing and Distilling Damping Structure
Physical understanding is crucial for decision making, yet vision models struggle to infer properties such as damping that govern how materials behave.WaveLLM: Wavelet-Domain LLM Entropy Modeling for Lossless Image Compression
Lossless image compression fundamentally relies on accurate entropy modeling, driving a recent shift toward large language model (LLM)-based methods.OS-Helix: Unifying GUI Interaction and Code Execution in Native Computer-Using Agents
Real desktop automation is neither purely visual nor purely programmatic.MMSearch-OPD: Easy Made Hard, Hard Made Learnable for Long-Horizon Multimodal Search Agents
Multimodal deep search is moving from short queries to long-horizon investigations that continually acquire evidence.Denoising Textures is a Different Ballgame Altogether!
The human brain effortlessly deciphers colors and textures from visual stimuli and reconstructs the world around us, yet preserving such details remains challenging in image denoising.FPG-Seg: Annotation-free Retinal Vessel Topology Segmentation
State-of-the art approaches to retinal vessel segmentation typically require extensive annotations, a highly time-consuming process, reliant on clinical expertise.SCOPE: Semantic Bounded Credit Optimization for Prompt Engineering in Text-to-image Generation
Reinforcement learning (RL) enables language models to improve text-to-image (T2I) generation by rewriting prompts for a frozen image generator.Beyond Pairwise Repulsion: Collective Diversity via Determinant Maximization in Diffusion Sampling
Strong guidance in text-to-image (T2I) diffusion models concentrates sampling toward high-density modes of the conditional distribution, collapsing independently sampled noise vectors onto nearly…Unsupervised Clustering of Public Transport Vehicles Using Deep Morphological Features and Color Histograms
Surveillance cameras along urban roads produce large volumes of unlabeled video that could support the monitoring of public transport, but grouping the observed vehicles into meaningful categories…MJev-Spatial: System One Spatial Intelligence via Native Attention Matching
Spatial intelligence lets an agent perceive and act in the physical world, and many of its judgments must be made at interaction rates: which spatial relation holds, how far an object is, or where…Routing Policy Optimization for Online Diffusion Reinforcement Learning
Reinforcement learning can align visual generators with reward signals beyond their pretraining objectives, but existing score-function methods typically introduce stochasticity by perturbing the…Grounded Human-Attributed Description and Activity Recognition in Videos
Understanding characteristics and activities of individuals in complex multi-person environments is crucial for real-world applications.ARC-SORT: Adaptive, Robust, Compensated Multi-Object Tracking with Interacting Multiple Models
Multi-object tracking in sports broadcasts is hard for two reasons: athletes move fast and change direction abruptly, and the camera pans and zooms at the same time.Velox: Spatial Memory Makes World Models Efficient
Video world models turn actions and camera motion into long visual rollouts, making video a natural interface for interactive simulation.Not Just a Subject: Capturing Adaptive Scene-Specific Variance for Visual Storytelling
Recent advancements in diffusion models have significantly improved text-to-image generation, enabling their application to visual storytelling, where coherent image sequences are generated from…AVC-Reward: Event-Centric Audio-Video Consistency Evaluation
As joint audio-video generation models become more capable, they can generate audio-visual scenes exhibiting three forms of complexity: multi-event composition, multi-layer audio mixture, and…Dense4D: Pixel-Level 4D Human Correspondence
Reconstructing human motion in 4D requires identifying the same surface points through articulation, deformation and changes in visibility.ACEdit: Stable Multi-Turn Image Editing via Asymmetric Conditioning
Image editing models produce impressive results for individual edits, but their quality often deteriorates over multiple editing turns.