Copertina

Beyond the Doors of Perception: Vision Transformers Represent Relations Between Objects

Fuente: arXiv

Salvato in:

Dettagli Bibliografici
Autori principali:	Lepori, Michael A., Tartaglini, Alexa R., Vong, Wai Keen, Serre, Thomas, Lake, Brenden M., Pavlick, Ellie
Natura:	Preprint
Pubblicazione:	2024
Soggetti:	Computer Vision and Pattern Recognition Artificial Intelligence
Accesso online:	Acceder al recurso
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

Deep Neural Networks Can Learn Generalizable Same-Different Visual Relations
di: Tartaglini, Alexa R., et al.
Pubblicazione: (2023)

I Walk the Line: Examining the Role of Gestalt Continuity in Object Binding for Vision Transformers
di: Tartaglini, Alexa R., et al.
Pubblicazione: (2026)

Uncovering Intermediate Variables in Transformers using Circuit Probing
di: Lepori, Michael A., et al.
Pubblicazione: (2023)

On the robustness of modeling grounded word learning through a child's egocentric input
di: Vong, Wai Keen, et al.
Pubblicazione: (2025)

Video Finetuning Improves Reasoning Between Frames
di: Yang, Ruiqi, et al.
Pubblicazione: (2025)

How Do Vision-Language Models Process Conflicting Information Across Modalities?
di: Hua, Tianze, et al.
Pubblicazione: (2025)

From Prediction to Understanding: Will AI Foundation Models Transform Brain Science?
di: Serre, Thomas, et al.
Pubblicazione: (2025)

Representative Attention For Vision Transformers
di: Li, Yuntong, et al.
Pubblicazione: (2026)

Diagnosing Bottlenecks in Data Visualization Understanding by Vision-Language Models
di: Tartaglini, Alexa R., et al.
Pubblicazione: (2025)

Capability $\neq$ Interpretability: Human Interpretability of Vision Foundation Models
di: Colin, Julien, et al.
Pubblicazione: (2026)

PLOOD: Partial Label Learning with Out-of-distribution Objects
di: Huang, Jintao, et al.
Pubblicazione: (2024)

ObjectTransforms for Uncertainty Quantification and Reduction in Vision-Based Perception for Autonomous Vehicles
di: Sahu, Nishad, et al.
Pubblicazione: (2025)

AnyDoor: Zero-shot Object-level Image Customization
di: Chen, Xi, et al.
Pubblicazione: (2023)

FSOD-VFM: Few-Shot Object Detection with Vision Foundation Models and Graph Diffusion
di: Feng, Chen-Bin, et al.
Pubblicazione: (2026)

The Components of Collaborative Joint Perception and Prediction -- A Conceptual Framework
di: Wan, Lei, et al.
Pubblicazione: (2025)

Evaluating Graphical Perception Capabilities of Vision Transformers
di: Poonam, Poonam, et al.
Pubblicazione: (2026)

Weakly-supervised Semantic Segmentation via Dual-stream Contrastive Learning of Cross-image Contextual Information
di: Lai, Qi, et al.
Pubblicazione: (2024)

Systematic Literature Review on Vehicular Collaborative Perception -- A Computer Vision Perspective
di: Wan, Lei, et al.
Pubblicazione: (2025)

Beyond First-Order: Learning Riemannian Geometries for Invariant Visual Place Recognition
di: Cheng, Jintao, et al.
Pubblicazione: (2026)

Fish2Mesh Transformer: 3D Human Mesh Recovery from Egocentric Vision
di: Jeong, David C., et al.
Pubblicazione: (2025)

ViTOC: Vision Transformer and Object-aware Captioner
di: Huang, Feiyang
Pubblicazione: (2024)

Object Referring-Guided Scanpath Prediction with Perception-Enhanced Vision-Language Models
di: Quan, Rong, et al.
Pubblicazione: (2026)

Temporal-Spatial Object Relations Modeling for Vision-and-Language Navigation
di: Huang, Bowen, et al.
Pubblicazione: (2024)

DoorDet: Semi-Automated Multi-Class Door Detection Dataset via Object Detection and Large Language Models
di: Zhang, Licheng, et al.
Pubblicazione: (2025)

AnywhereDoor: Multi-Target Backdoor Attacks on Object Detection
di: Lu, Jialin, et al.
Pubblicazione: (2024)

AnywhereDoor: Multi-Target Backdoor Attacks on Object Detection
di: Lu, Jialin, et al.
Pubblicazione: (2025)

Beyond Grids: Exploring Elastic Input Sampling for Vision Transformers
di: Pardyl, Adam, et al.
Pubblicazione: (2023)

R-LiViT: A LiDAR-Visual-Thermal Dataset Enabling Vulnerable Road User Focused Roadside Perception
di: Mirlach, Jonas, et al.
Pubblicazione: (2025)

DOPE: Dual Object Perception-Enhancement Network for Vision-and-Language Navigation
di: Yu, Yinfeng, et al.
Pubblicazione: (2025)

Seeing Beyond the Scene: Analyzing and Mitigating Background Bias in Action Recognition
di: Zhou, Ellie, et al.
Pubblicazione: (2025)

Synchronized Object Detection for Autonomous Sorting, Mapping, and Quantification of Materials in Circular Healthcare
di: Zocco, Federico, et al.
Pubblicazione: (2024)

Can Transformers Capture Spatial Relations between Objects?
di: Wen, Chuan, et al.
Pubblicazione: (2024)

Retina Vision Transformer (RetinaViT): Introducing Scaled Patches into Vision Transformers
di: Shu, Yuyang, et al.
Pubblicazione: (2024)

Visual-Word Tokenizer: Beyond Fixed Sets of Tokens in Vision Transformers
di: Gee, Leonidas, et al.
Pubblicazione: (2024)

A Simple yet Effective Network based on Vision Transformer for Camouflaged Object and Salient Object Detection
di: Hao, Chao, et al.
Pubblicazione: (2024)

Can Modern Vision Models Understand the Difference Between an Object and a Look-alike?
di: Cohen, Itay, et al.
Pubblicazione: (2025)

Choosing the right basis for interpretability: Psychophysical comparison between neuron-based and dictionary-based representations
di: Colin, Julien, et al.
Pubblicazione: (2024)

3D Hand Mesh-Guided AI-Generated Malformed Hand Refinement with Hand Pose Transformation via Diffusion Model
di: Feng, Chen-Bin, et al.
Pubblicazione: (2025)

Looking Locally: Object-Centric Vision Transformers as Foundation Models for Efficient Segmentation
di: Traub, Manuel, et al.
Pubblicazione: (2025)

GUMBEL-NERF: Representing Unseen Objects as Part-Compositional Neural Radiance Fields
di: Sekikawa, Yusuke, et al.
Pubblicazione: (2024)