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 118
STRIDE: Evaluating Spatiotemporal Reasoning in Driving Edge Cases
In autonomous driving, perceiving surrounding objects is not enough: failing to understand how they move and interact over time can lead to dangerous decisions.Replay Pruning and Few-Bit Integer Inference for Hardware-Efficient Speed-Sign Recognition
Speed-limit sign recognition on an automotive camera system-on-chip (SoC) must fit a detector and a classifier (the reader) into the memory, arithmetic, and energy budgets of the device.VISTA: A Multimodal Egocentric Benchmark for Goal-Oriented Perception and Assistance to Blind and Low-Vision Users
Blindness and low vision limit many people's ability to complete daily tasks, motivating AI assistants that provide useful guidance.VTrajEmbed: Aligning Text with Video Object Trajectories via Spatiotemporal Embeddings
Fine-grained alignment between text and video object trajectories is a core challenge in multimodal understanding.Variational and Decomposed method for Mitigating Bimodal Bias in Robust Visual Question Answering
Visual question answering (VQA) models are known to suffer from the bias issue, which refers to overfitting the regularities of frequent patterns.Measurement-Adaptive Light-Cone Transform for Robust Non-Line-of-Sight Imaging
Practical non-line-of-sight (NLOS) measurements are affected by noise and deviations from idealized light transport, which can degrade reconstruction with conventional light-cone transform (LCT)…HAPACT: A Benchmark For Human-Centric Physical Impact Localization in Movies
Physical reasoning about humans in videos has largely focused on everyday interactions, where contact, pressure, pose, and motion support embodied perception and contact-aware applications.COMET: Decoupled Distillation, Routing, and Capacity Control for Task-Agnostic Continual Vision--Language Learning
Vision-language models (VLMs) such as CLIP retain zero-shot recognition ability, but their open-world use often requires task-agnostic continual learning: tasks arrive sequentially, past data are…MaskMerge: Structure-aware Token Merging for Efficient Instance Segmentation
Token merging improves the efficiency of Vision Transformers by combining redundant tokens, but existing methods largely rely on feature similarity to determine which tokens to merge.ODSS-Net: Orthogonally Decoupled Shared-Specific Representations for Multi-Modal Object Re-Identification
Multi-modal object re-identification (ReID) leverages complementary information from heterogeneous sensors.DICL-Qwen3VL: Decoupled Confidence Calibration for Interpretable Workwear Detection
Poor illumination and occlusion obscure clothing cues in indoor work sites, while diverse clothing styles complicate workwear compliance judgments.MambaAct: Efficient Mamba Action Experts for Flow-Matching Vision-Language-Action Models
Vision-language-action (VLA) models have shown strong promise for generalist robotic manipulation, but their inference cost remains a major bottleneck for real-time control.Query-adaptive Recurrent Tokenization
Visual information worth extracting from an image and the token budget it warrants depend on the text query.Stabilizing Illumination Conditioning in SSM-Based Low-Light Image Enhancement with Bottleneck Prompt Sidecars
Low-light image enhancement (LLIE) requires more than brightness amplification because real low-light images often exhibit spatially varying illumination, amplified noise, color distortion, and…ANCHOR: Audio-Visually Grounded Chain-of-Thought Reasoning Benchmark
Multimodal large language models (MLLMs) perform well on audio-visual question answering, but correct answers do not necessarily imply that their stated reasoning is grounded in relevant perceptual…Sink-Sparse Hybrid Attention for Efficient Inference in T2I/T2V Diffusion Transformers
Diffusion Transformers (DiTs) have become a common backbone for high-quality text-to-image and text-to-video generation, but repeated dense self-attention remains a major inference bottleneck as…How Murky Before a VLM Knows It Cannot See? Accuracy, Confidence and Abstention on a Physical Visibility Axis
Robustness studies of vision-language models (VLMs) grade degradation on nominal severity scales ("level 1-5") that carry no physical units, and they rarely ask whether a model's confidence follows…UniField++: A Unified Agentic Framework with Loop Reasoning for MRI Field-Strength Enhancement
MRI field-strength enhancement seeks to combine the accessibility of low-field scanners with the image quality of high-field scanners.A100: A Hybrid Vision Foundation Model for Agricultural Plant Image Analysis
The use of accurate vision models for crop monitoring, disease diagnosis, and plant phenotyping in agriculture is hindered by the lack of expertly annotated data, especially in developing countries.BRICE: Brain-inspired Recurrent Illusory Contour Encoder for Point Cloud Completion
Mainstream point cloud completion methods are unanimously based on deep learning architectures.