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computer vision

3,363 papers

#machine learning Preprint Open access Sep 2026

Unexplored flaws in multiple-choice VQA make benchmarking unreliable

Previous works identify sensitivity to option order as a key issue in multiple-choice VQA (MC-VQA) evaluation and propose protocols to mitigate this effect. We show that such mitigation is insufficient to ensure the validity of MC-VQA as a reliable benchmark for Multimodal Large Language Model (MLLMs): performance rema...

Fabio Rosenthal, Sebastian Schmidt, Thorsten Graf et al. · 0 citations

ComplicitSplat: Downstream Models are Vulnerable to Blackbox Attacks by 3D Gaussian Splat Camouflages

ComplicitSplat is introduced, the first attack that exploits standard 3DGS shading methods to create viewpoint-specific camouflage to embed adversarial content in scene objects that are visible only from specific viewpoints and without requiring access to model architecture or weights.

Matthew Hull, Haoyang Yang, P. Mehta et al. · 1 citation
#machine learning Preprint Open access Sep 2026

ControlTac: Scaling Tactile Data with Physically Controlled Tactile Image Generation

Vision-based tactile sensing is widely used in perception, reconstruction, and robotic manipulation, yet collecting large-scale tactile data remains costly due to diverse sensor-object interactions and inconsistencies across sensor instances. Existing approaches to scaling tactile data---simulation and free-form tactil...

Dongyu Luo, Kelin Yu, Amir-Hossein Shahidzadeh et al. · 0 citations

Neural Field Tokenizations with Hierarchy and Spatial Locality Priors

It is argued that locality and hierarchy are useful priors for learning field representations that can be injected without compromising modality-agnosticism in LH-NeF, a framework to learn general-purpose tokenized representations of continuous signals.

Alonso Urbano, David W. Romero, Max Zimmer et al. · 1 citation
#machine learning Preprint Sep 2026

Charts Are Beyond Pixels: Probing for Layer-Wise Chart Understanding and Editing

Charts are structured visual compositions whose elements have distinct functional roles, semantic correspondences, and visibility relations. This structural view motivates evaluating whether models can understand and manipulate charts at the layer level. Existing chart benchmarks, however, primarily assess the correctn...

Xiao-Chuan Zhong, Yi-Fan Hou, Chen-Xi Pang et al. · 0 citations
#machine learning Preprint Open access Sep 2026

Temporal State Transport in Video Generation: Diagnosing and Correcting Spectral Imbalance

Reliable video generation requires more than high-quality frames to form a coherent story: a model must maintain a persistent state, transporting visual attributes such as identity, scene layout, motion, and fine details across time. Existing training-free methods mainly strengthen cross-frame attention or analyze loca...

Luyao Tang, Bingjun Luo, Dong Yi et al. · 0 citations
#machine learning Preprint Sep 2026

To Adapt or Not to Adapt? Selective Adaptation for Vision-Language Models

This work proposes Cross-Augmentation Similarity (CAS), a simple baseline that performs adaptation only when predictions across augmented views exhibit low similarity, which not only preserves but in some cases improves overall accuracy, even when skipping nearly 85% of the adaptation process.

Si-Ru Jiang, Yu-Wei Liang, Jian Liang et al. · 1 citation
#machine learning Preprint Sep 2026

CoVeR: Coverage-Based Token Pruning for Multi-View 3D Reasoning in VLMs

It is shown that spatial coverage is associated with 3D reasoning performance and CoVeR, a deterministic, training-free selector that uses only token coordinates, with no learned signals is introduced, which outperforms prior SOTAs on all three 3D reasoning benchmarks and generalizes as a plug-and-play module tested ac...

Nhat-Tan Bui, Varshini Elangovan, Arun Reddy Anugu et al. · 0 citations
#machine learning Preprint Sep 2026

ActionSplice: In-Flight Action Editing for Interactive World Models

This work introduces \emph{ActionSplice], which edits the interrupted state through Counterfactual State Transport (CST), a lightweight corrector that moves the interrupted solver state toward the matched counterfactual solver state induced by the revised action at the same solver step.

P. Taghavi, Ting-Yu Guo, Jonas Lossner et al. · 0 citations
#machine learning Preprint Sep 2026

Marigold V2: Revisiting Diffusion Transformers for Monocular Depth Estimation

Marigold V2 achieves state-of-the-art results when applied to other dense regression tasks, such as surface normals estimation and intrinsic image decomposition, and achieves state-of-the-art results when applied to other dense regression tasks, such as surface normals estimation and intrinsic image decomposition.

Igor Pavlovic, Thiemo Wandel, Anton Obukhov et al. · 1 citation · ⚡1
#machine learning Preprint Sep 2026

A Quantitative Evaluation Framework for Temporal Explainability in Echocardiographic Video Segmentation

A preliminary quantitative framework for temporal explainability is established and temporal-aware XAI methods that explicitly account for evolving representations in medical video models that explicitly account for evolving representations in medical video models are motivated.

Jiyoo Noh, Jonathan H. Chan · 0 citations

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Microsoft Research Blog Oct 6, 2026

What AI gets wrong and what failure teaches us

Jennifer Neville did not want to go into computer science—but that’s exactly where she landed. Neville discusses the starts and stops that led to her professional sweet spot and her work identifying “surprising failures” making it hard for AI to handle complexity.  The post What AI gets wrong and what failure teaches us appeared first on Microsoft Research.

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