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: 4,996 arXiv preprints and 4 OpenAlex records.
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Newest papers, page 249
OmniTaskonomy: When Does Visual Generation Improve Visual Understanding?
Training a model to generate visual content can encourage it to learn rich perceptual capabilities related to geometry, spatial relationships, and objectness; yet, its benefits for visual…VISTA: Internalizing Collective Visual Experience via On-Policy Distillation for Active Multimodal Agents
Active multimodal agents use visual tools to acquire task-relevant evidence while reasoning.From Routing Signals to Selective Review: Visual regrounding in MoE VLMs
Vision-language models (VLMs) may accept false visual premises, answering questions about a target object's color, count, location, or state even when it is absent.Self-Aligned Forcing: Streaming Video Diffusion with Differentiable Noisy History
Autoregressive video diffusion enables interactive streaming generation, but suffers from error accumulation over long rollouts.GA-EIRFS: A Geometry-Augmented Repeat-Factor Sampling Method for Long-Tailed LiDAR 3D Object Detection
Long-tailed 3D object detection is treated as a class-frequency problem, but LiDAR supervision quality depends on object observability: similar frequencies can hide different geometric evidence.VideoLoop: Looped Working Memory Against Semantic Thrashing in Long-Form Video Agents
Long-form video understanding requires multimodal agents to iteratively gather evidence over many reasoning steps.HelixWorld: A Real-time Interactive Audio-Visual World Model
World simulation is inherently multisensory, demanding synchronized visual and acoustic dynamics in real time.CLeaR: A Unified Framework for Resolving the Leakage-Degradation Dilemma in Style Transfer
Style transfer aims to render target content in the style of a reference image, but existing methods often suffer from content leakage, where objects, layouts, or semantics from the style reference…Breaking the Uniformity Trap: Scaling Video Diffusion Model via SplitMoE
Mixture-of-Experts (MoE), popularized by large language models, is a promising paradigm for scaling visual generative models.LIFT: Layout-In-Future Video Generation under Large Viewpoint Change via On-Policy Self-Distillation
We introduce LIFT, a unified image-to-video generation framework that complements camera control with Layout-In-FuTure control, enabling users to specify what should appear in a future view and…FracGen: Learning How Objects Stretch and Tear with Physics-Informed Video Generation
We introduce FracGen, a fracture-aware video generation model that produces plausible, controllable fracture dynamics from a single image of an intact object, conditioned on physics signals.PowerSim: Differentiable Physics Simulation and Rendering with Power Diagrams
We introduce PowerSim, a method to bring physically grounded, differentiable dynamics to PowerFoam's power diagram based 3D representation.LongLive-Plug: Once-for-All Distillation for Video Generation
Video diffusion models are increasingly developed into specialized models for diverse downstream tasks, and this development often includes a distillation stage, for example to accelerate sampling…Beyond the Timeline: Augmenting Long-Video Memory with Grounded Entity Biographies
Answering questions about long videos often requires connecting events involving the same objects across hours or days.DMA$^2$: Pixel-space Distribution Matching with Adversarial and Anchor Losses
Distribution matching distillation (DMD) provides a general framework for few-step diffusion generation, but its modern text-to-image instantiations have been developed primarily around latent…Rethinking Representations for World-Action Modeling
World-action models jointly learn robot policies and predict future observations, making the representation space an interface between control and prediction.Cropland PAtteRNS: Parallel Dimensional Attention Networks and Attention to Dataset Disparity for Crop Segmentation in Satellite Imagery Time Series Data
The landscape of satellite imagery time series datasets and boundary-pushing architectures for cropland segmentation has never been richer.Adversarial Training for Pixel Diffusion
Pixel diffusion models generate RGB images directly, avoiding the bottleneck of an autoencoder, yet their outputs still systematically underrepresent fine-scale natural-image statistics.Counterfactual Video Generation Enables Scalable Humanoid Loco-Manipulation
Teaching humanoids loco-manipulation skills, such as carrying diverse objects, via visual imitation is a promising path toward generalist robots.Imagine3D-LLM: Teaching MLLMs to Imagine 3D Scenes Before Answering
Reasoning about the 3D world from multi-view images remains a fundamental challenge for Multimodal Large Language Models (MLLMs).