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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 158
Recovering Low-Bit Failures in Vision-Language-Action Policies via Quantization-Conditioned Reinforcement Learning
Quantization lowers deployment costs of vision-language-action (VLA) policies but can compromise task completion.Rethinking Human Intent-to-CAD: Parametric CAD Model Generation via Cooperative Multi-Task Alignment and Spatial-Aware Reinforcement Learning
Parametric Computer-Aided-Design (CAD) modeling from human intent remains challenging, particularly during the conceptual design stage, where design goals are expressed through incomplete and…PhySimCode: A Benchmark and Evaluation Method for Physics Video to Code Generation
Multimodal large language models (MLLMs) are good at video understanding and code generation, but it remains unclear whether they can recover the physical laws underlying videos, a capability…Visually Legible but Adversarial: Watermark-Constrained Attacks on End-to-End VLMs for Document Understanding
Visible watermarks convey document ownership, confidentiality, and status, but can also carry adversarial signals.ScenePlacer: Reformulating Scene-Level Object Pose Estimation as Visibility Field Learning
We present ScenePlacer, a framework for scene-level pose estimation of objects generated by state-of-the-art native shape generation models, placing generated 3D objects into scenes given a partial…RSAJEV: Training-Free Abstaining Prototype Memory for Eliminating Silent Hallucination in JEV-Based Remote Sensing Classification
Scene classification of remote sensing imagery with multimodal large language models (MLLMs) is formulated as a single-forward-pass decision problem: candidate class names are lettered options in…SpikeOcc: Towards Resilient Multimodal 3D Occupancy Perception via Spiking Experts
Multimodal 3D occupancy prediction underpins safe autonomous driving through comprehensive scene understanding.Frozen History: When Temporal Losses Stop Accumulation in Learned Real-Time Supersampling
Learned real-time supersampling accumulates jittered low-resolution samples along motion vectors.SlotAVS: Object-Centric Audio-Visual Segmentation via Bi-Modal Slot Attention
Audio-Visual Segmentation (AVS) requires predicting pixel-wise masks of sounding objects by grounding acoustic signals in visual space.Hand2Robot: Object-Centric 4D Hand Reconstruction from Human Demonstrations for Robotics
Human demonstrations can capture task-relevant manipulation without using the target robot, but the recorded hand motions cannot directly serve as robot action supervision.Data-Centric Recursive Self-Improvement for Navigation via Policy-Synchronized Language-Action Dual Bootstrapping
Vision-language navigation requires agents to follow natural-language instructions to reach target locations, making high-quality language supervision essential.Reference-Efficient Multimodal Bitstream-Corrupted Video Recovery via Depth-Conditioned Adaptation
Recovering visually faithful content from damaged video bitstreams is important for reliable multimedia communication and storage.Totem: Object-Centric 3D Memory for World-Consistent Video Generation
Generating coherent videos grounded in a unified underlying world remains a major challenge, particularly under large viewpoint changes, where existing methods often struggle to maintain stable…Adaptive Look, Flexible Thought: Learning How and How Long to Think in Multimodal Reasoning
The introduction of long chain-of-thought (CoT) reasoning and external tools has substantially improved the performance of multimodal large language models (MLLMs) on general and reasoning tasks.ChangeT$^3$: Evaluating Vision Test-Time Training for Remote Sensing Change Detection
Bitemporal remote sensing change detection requires representations that preserve spatial detail while capturing contextual information relevant to changes between acquisitions.ML-CLAPPS: A Probabilistic Framework for Imbalanced Multilabel Learning under Class Prioritization
Real-world datasets often exhibit severe class imbalance, degrading the performance of deep learning models, particularly on rare classes.Mobility Helps Learning: Unsupervised Model Adaptation for Object Recognition via Movement
Movable agents, such as autonomous vehicles and robots, should be able to autonomously adapt their pre-trained object recognition models to new environments without human annotations.Sharper Frames, Worse Rooms: Viewpoint Coverage Dominates Image Quality in Feed-Forward 3D Reconstruction
Grounded spatial reasoning about indoor scenes rests on a geometric reconstruction that the multimodal system does not itself produce.Learning Multimodal Sensor Fusion with JEPA Representations for Breathing Activity and Pose Recognition
Predictive video representations do not by themselves specify how a multimodal system should handle missing sensors.Gen Through the Lens: Camera-Controllable Video Generation via Cross-Coordinate Conditioning Fusion
We present Gen Through the Lens, a camera-controllable image-to-video generation framework that synthesizes videos from a given reference image while enabling realistic and physically consistent…