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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: 4,996 arXiv preprints and 4 OpenAlex records.
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Newest papers, page 222
FiVOS: A Fish Segmentation Algorithm Based on Interactive Video Object Segmentation and Filter Enhancement
With the continuous expansion of aquaculture, precise and efficient monitoring of fish behavior has become increasingly critical for improving farming efficiency and reducing economic losses.SALD: Self-Referenced Advantage Learning for Diffusion Models
Recent work on language-model adaptation has shown that single models can obtain informative training signals by evaluating their behavior in demonstrationor feedback-augmented contexts, with the…VTR-Bench: A Systematic Benchmark for Evaluating Visual Text Rendering in Video Generation
Recent video generation models can produce highly realistic videos from natural language instructions, with visual quality approaching cinematic standards.FedCKA: Representation-Guided Layer Personalization for Federated 3D Perception Across Driving Domains
Robust perception in intelligent vehicles demands 3D object detectors that remain dependable under domain shifts, such as changes in time of day, location, or weather.VoxelSynth3D: Interpretable Volumetric Image-Domain Metal Artifact Reduction with a Paired Synthetic CLINIC-Metal Benchmark
Metal artifacts in postoperative musculoskeletal CT obscure bone-implant and adjacent soft-tissue interfaces.SuperMotion: Source-Preserving Denoising for Text-Driven Human Motion Editing
Text-driven human motion editing aims to realize a requested change while preserving compatible source content.Towards Reliable Vision-Language Models for Autonomous Driving
Vision-Language models (VLMs) are increasingly being explored in autonomous driving for tasks such as scene understanding, driving reasoning, decision-making, and end-to-end driving.Synthetic training for long-tail haemorrhagic lesion segmentation in data-scarce settings
Cerebral microbleeds (CMBs) and cortical superficial siderosis (cSS) are imaging markers of cerebral small vessel disease, but their automated segmentation is limited by the scarcity of positive…Revisiting Cross-Reconstruction for Generalizable Deepfake Detection
Existing image forgery detectors often suffer from generalization to unseen manipulation methods due to the limited ability to capture transferable forensic cues.PAGER: Partial-to-global Alignment via Geometric and Relational Distillation
Pretrained 3D encoders are typically developed on globally reconstructed scenes expressed in a consistent world coordinate frame, whereas embodied systems must reason from partial…Two Routes to the Middle: Placement Search and Brain Readouts Converge on Where Continual Learners Should Specialize
Continual learners that keep a task-specific adapter in every block of a pre-trained vision transformer accumulate storage linearly with the number of tasks; keeping task-specific adapters in only a…Before It Fades: Reinforcing Temporal Representations at Inference Time in VideoLLMs
Video Large Language Models (VideoLLMs) receive frames in sequential order and interpret how visual content evolves along the temporal axis, yet temporal reasoning remains a persistent weakness…Hob-VL: A Benchmark for Visually Grounded Boolean Reasoning
Reliable visual reasoning requires composing multiple visual observations and returning consistent answers to logically equivalent questions.Oneira: From Open-Ended Generation to Open-World Interaction in Video World Models
Generative video world models can now synthesize open-ended environments that agents can navigate and interact with in simple ways.Beyond Domain-Level Adaptation: Margin-Oriented Semantic-Appearance Interaction Correction for Personalized Federated Vision-Language Models
Federated parameter-efficient fine-tuning enables distributed clients to adapt pretrained vision-language models without sharing raw data or updating the full backbone.Fusing Visual and Textual Representations via Multi-layer Fusing Transformers for Vietnamese Visual Question Answering
In recent decades, artificial intelligence has made significant progress in understanding and interacting with images.Not All Error Yields to Scale: Where Scaling Stops in Vision-Language Inference
Vision-language models (VLMs) face a fixed-budget trade-off between processing more visual information for fine-grained perception and using a larger language backbone for complex reasoning.DiVid: Diagnosing Dimension-Specific Diversity Collapse in Video Generation Models
Despite remarkable progress, video generation models often produce highly similar outputs when repeatedly sampled from the same prompt, limiting their usefulness for creative exploration.Do MLLM Judges Judge the Edit? Auditing Bias in Image Editing Evaluation with Verified Quality Preservation
Multimodal large language models (MLLMs) are increasingly used as automated judges for instruction-based image editing and as reward signals for model training.When Text-to-Image Helps Editing: The Effects of Conditioning During Denoising
Unified models are trained for both instruction-based image editing and text-to-image (T2I) generation, but standard editing pipelines keep source-image conditioning throughout denoising.