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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 165
Fix the Match, Not the Solver: STITCH -- a Self-Supervised Compatibility Measure for Eroded Visual Puzzles
Unlike the clean and pixel-aligned complete pieces of standard jigsaw benchmarks, real-world puzzle fragments lose their boundary regions to erosion, destroying the signal that classical…CompactSplat: Spatially Adaptive Gaussian Distribution for Feedforward Scene Reconstruction
Reconstructing 3D scenes from sparse views without per-scene optimization remains highly challenging, especially for recovering accurate geometry and fine textures.High-Throughput Generative Video Super-Resolution on a Single Consumer GPU
Generative video super-resolution (VSR) can recover visually compelling high-frequency detail by leveraging diffusion priors, but iterative sampling and heavy spatio-temporal coupling make practical…MixTok: Adaptive Visual Tokenization with Global 1D Tokens and Sparse 2D Refinement
Efficient visual tokenization requires balancing representation compactness with the preservation of fine-grained image content.Destination-Conditioned Adaptation with Semantic-Geometric Alignment for Generative Inbetweening
Generative inbetweening aims to synthesize temporally coherent intermediate frames between a start frame and a target frame.Golden Anchor for Video Generation
Video generation supports digital content creation, with applications in virtual avatars, AI-driven filmmaking, interactive game engines, and world models.Complexity-Calibrated Reconstruction Discrepancy for No-Reference Point Cloud Quality Assessment
The discrepancy induced by surface reconstruction in a distorted point cloud is jointly influenced by its intrinsic structural complexity and signal degradation.Multi-Modal Graph Neural Network-Inspired Vessel Identification and Tracking for UAV-Based Maritime Surveillance
The unmanned aerial vehicle (UAV)-based maritime surveillance is becoming an important part of maritime Internet of Things (IoT) and intelligent transportation systems.Automated Detection and Encoding of Cartographic Signs in Historical Maps
Symbols and icons in archival maps represent an expansive source of evidence for historical geography.FPD-Drive: Future Policy Distillation for End-to-End Autonomous Driving
End-to-end autonomous driving models are typically trained on real-world driving logs, which record only the trajectory actually executed in each scene.The Predictability Bias of Joint-Embedding Predictive Learning in Medical Imaging
Joint-embedding predictive architectures (JEPAs) learn by predicting teacher representations of masked regions from visible context.Jag: Direct Box Prediction for Efficient Visual Grounding
Visual grounding combines image--language understanding with geometric prediction, yet autoregressive multimodal models often express a box as a coordinate sequence.Deep Learning Approach for RealTime Contraction Detection in Laboring Dairy Cattle
Currently, the animal production sector is undergoing rapid development of techniques that allow automatic monitoring of animal behaviour and health.Vision Transformers Learn Word Meaning from Images Alone
Can a vision model learn what words mean from pixels alone?Beyond a Single Crop: Contextualized Embeddings for Player Re-Identification
Person re-identification is typically addressed by learning identity-discriminative embeddings from individual person crops.Dual-Stream Memory for Vision-Language-Action Policies
Memory-dependent manipulation requires a policy to track execution state and recover visual evidence that is no longer observable.SheafPrune: Sheaf-Guided Graph Propagation for Visual Token Pruning
Multimodal large language models process the complete visual token sequence, increasing prefill cost even when many tokens are irrelevant to the instruction.CV-OPD: Contrastive Vision On-policy Distillation
On-policy distillation (OPD) reveals versatility and convenience during VLM post-training, providing dense supervision for student from teacher.ConClick: Element-Wise Contrastive Learning Improves GUI Grounding
GUI grounding, the task of locating the interface element specified by a user instruction, is a fundamental capability of GUI agents.OWLET: On-Policy Weighted Learning via Evidence Transfer for Video Large Language Model Post-Training
Post-training has become a key stage for eliciting reasoning capabilities in Video Large Language Models (Video-LLMs).