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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 9
Semantic Prior-Guided Incomplete Cross-Modal Retrieval with Noisy Labels
Cross-modal retrieval (CMR) aims to bridge the semantic gaps between modalities by learning shared representations.ReactWorld: Structuring Interaction Responses for Embodied Video Generation
Embodied video world models predict scene changes caused by robot actions, yet generated object responses may remain inconsistent with task intent and contact dynamics.RDT-3D: Resolution-Decoupled Training for High-Fidelity 3D Geometry Generation
High-fidelity 3D geometry generation requires maintaining global structural coherence alongside fine-grained surface details.PTQ4SAM3: Semantics-Preserving Post-Training Quantization for Segment Anything Model 3
Segment Anything Model 3 (SAM 3) can segment objects from text prompts and track them across video, but its memory and computation costs make deployment difficult.Grounding in the Dark: Text-Only Training for Zero-Shot Video Temporal Localization
Video-LLMs are typically trained on paired video-text data for temporal tasks, yet collecting precise temporal annotations and training on large-scale video datasets are both costly.DSRS: Teaching MLLMs to Perceive, Reason, and Segment in Complex Driving Scenes
Existing reasoning segmentation frameworks typically employ multimodal large language models (MLLMs) with broad world knowledge to extract semantics in a human-like manner and generate corresponding…Reasoning-Aware Cross-Modal Association Unlearning in Multimodal Large Reasoning Models
Multimodal large reasoning models (MLRMs) integrate visual inputs with textual and parametric knowledge, allowing sensitive information to be accessed through cross-modal associations during…Rohbau3D-Semantics: Dense Semantic and Instance Labels for Point Clouds of Indoor Shell Construction Scenes
We present the Rohbau3D-Semantics dataset, which adds dense semantic and instance-level labels to laser scans of the previously released Rohbau3D domain data from shell construction sites.Annotator-Free Object Detection via Foundation Model Collaboration
Object detection research remains constrained by high annotation costs and the closed-set assumptions of supervised models, limiting scalability to novel categories.BiCG-Net: Target-Specific Image Quality Assessment via Observation Modeling and In-Image Differencing
We estimate the quality of a specific target region (e.g., a train body) in an image, rather than the whole image.Cross-Modal Semantic Successive Refinement for Generative Image Communication over Underwater Acoustic Channels
Underwater acoustic communication faces challenges such as limited available bandwidth and complex channel environments, which impose demanding requirements on efficient image transmission and…FedXCrop: Privacy-Preserving Crop Disease Detection via Federated Learning with Post-Aggregation Explainability under Non-IID Farm Distributions
Deep learning can classify crop diseases accurately from benchmark leaf images, but centralized training requires farms to share raw data, and predictions without explanations offer limited support…Homology Features for X-Ray Hyperspectral Images Segmentation
Characterizing Multi-Energy X-ray Transmission (XRT) hyperspectral images presents significant challenges for traditional classification frameworks due to high-dimensional redundancy and non-linear…CAPE-JEPA - Cross-modal Adversarial Probabilistic Embedding JEPA
Cross-modal remote sensing image retrieval (RS-CMIR) requires representations that are simultaneously modality-invariant and semantically discriminative, despite the profound physical gap between…Learning Noise Optimization for Reward Alignment in Few-Step Generative Models
Reward alignment for diffusion- and flow-based generative models is often formulated over stochastic trajectories, making it less suitable for few-step deterministic generators.CrossPressor: Scalable Cross-View Fusion for Feed-Forward 3D Gaussian Splatting
Feed-forward 3D Gaussian Splatting (3D-GS) becomes increasingly difficult to scale to long multi-view sequences.A Systematic Benchmark for Evaluating Multimodal Personalized Reasoning of Vision-Language Models
People often make decisions by holistically reasoning over heterogeneous forms of personal information.NextGAN: Towards Simple and Scalable GAN Training for Image and Video Generation
Adversarial training enables one- and few-step image and video generation, but conventional adversarial losses supervise critic values without directly specifying the gradients used to update the…Quo Vadis, Driving Scene Reconstruction? Occlusion-Aware Gaussian Densification
While recent feed-forward 3D Gaussian Splatting methods enable efficient driving-scene reconstruction from surround-view images, their reliance on a single observation fundamentally hinders…MonoLaDN: Language-Guided DeNoising for Monocular 3D Object Detection
Monocular 3D object detection offers a low-cost route to 3D perception, but it remains fundamentally ill-posed, since depth must be inferred from a single view.