Copertina

CD-Buffer: Complementary Dual-Buffer Framework for Test-Time Adaptation in Adverse Weather Object Detection

Fuente: arXiv

Salvato in:

Dettagli Bibliografici
Autori principali:	Song, Youngjun, Kim, Hyeongyu, Hwang, Dosik
Natura:	Preprint
Pubblicazione:	2026
Soggetti:	Computer Vision and Pattern Recognition Machine Learning
Accesso online:	Acceder al recurso
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

Buffer layers for Test-Time Adaptation
di: Kim, Hyeongyu, et al.
Pubblicazione: (2025)

AcTTA: Rethinking Test-Time Adaptation via Dynamic Activation
di: Kim, Hyeongyu, et al.
Pubblicazione: (2026)

MUST: Modality-Specific Representation-Aware Transformer for Diffusion-Enhanced Survival Prediction with Missing Modality
di: Kim, Kyungwon, et al.
Pubblicazione: (2026)

TWINGS: Thin Plate Splines Warp-aligned Initialization for Sparse-View Gaussian Splatting
di: Kim, Hyeseong, et al.
Pubblicazione: (2026)

Buffer-free Class-Incremental Learning with Out-of-Distribution Detection
di: Gupta, Srishti, et al.
Pubblicazione: (2025)

Ranked Entropy Minimization for Continual Test-Time Adaptation
di: Han, Jisu, et al.
Pubblicazione: (2025)

Buffer replay enhances the robustness of multimodal learning under missing-modality
di: Zhu, Hongye, et al.
Pubblicazione: (2025)

Mitigating the Bias in the Model for Continual Test-Time Adaptation
di: Chung, Inseop, et al.
Pubblicazione: (2024)

When Test-Time Adaptation Meets Self-Supervised Models
di: Han, Jisu, et al.
Pubblicazione: (2025)

Robustness of Object Detection of Autonomous Vehicles in Adverse Weather Conditions
di: Pettersen, Fox, et al.
Pubblicazione: (2026)

Reshaping the Online Data Buffering and Organizing Mechanism for Continual Test-Time Adaptation
di: Zhu, Zhilin, et al.
Pubblicazione: (2024)

VLM-Pruner: Buffering for Spatial Sparsity in an Efficient VLM Centrifugal Token Pruning Paradigm
di: Wu, Zhenkai, et al.
Pubblicazione: (2025)

WeatherProof: Leveraging Language Guidance for Semantic Segmentation in Adverse Weather
di: Gella, Blake, et al.
Pubblicazione: (2024)

Entropy is not Enough for Test-Time Adaptation: From the Perspective of Disentangled Factors
di: Lee, Jonghyun, et al.
Pubblicazione: (2024)

Backpropagation-Free Test-Time Adaptation via Probabilistic Gaussian Alignment
di: Zhang, Youjia, et al.
Pubblicazione: (2025)

Two Simple Principles for Diffusion-Based Test-Time Adaptation
di: Song, Kaiyu, et al.
Pubblicazione: (2023)

AutoWeather4D: Autonomous Driving Video Weather Conversion via G-Buffer Dual-Pass Editing
di: Liu, Tianyu, et al.
Pubblicazione: (2026)

MedBN: Robust Test-Time Adaptation against Malicious Test Samples
di: Park, Hyejin, et al.
Pubblicazione: (2024)

When and Where to Reset Matters for Long-Term Test-Time Adaptation
di: Lim, Taejun, et al.
Pubblicazione: (2026)

Test-Time Adaptation for Depth Completion
di: Park, Hyoungseob, et al.
Pubblicazione: (2024)

Towards Reliable Test-Time Adaptation: Style Invariance as a Correctness Likelihood
di: Nam, Gilhyun, et al.
Pubblicazione: (2025)

Restoring Vision in Adverse Weather Conditions with Patch-Based Denoising Diffusion Models
di: Özdenizci, Ozan, et al.
Pubblicazione: (2022)

UniTTA: Unified Benchmark and Versatile Framework Towards Realistic Test-Time Adaptation
di: Du, Chaoqun, et al.
Pubblicazione: (2024)

BECoTTA: Input-dependent Online Blending of Experts for Continual Test-time Adaptation
di: Lee, Daeun, et al.
Pubblicazione: (2024)

Self-Bootstrapping for Versatile Test-Time Adaptation
di: Niu, Shuaicheng, et al.
Pubblicazione: (2025)

Parameter-Selective Continual Test-Time Adaptation
di: Tian, Jiaxu, et al.
Pubblicazione: (2024)

On the Adversarial Risk of Test Time Adaptation: An Investigation into Realistic Test-Time Data Poisoning
di: Su, Yongyi, et al.
Pubblicazione: (2024)

Learning to Generate Gradients for Test-Time Adaptation via Test-Time Training Layers
di: Deng, Qi, et al.
Pubblicazione: (2024)

A-BDD: Leveraging Data Augmentations for Safe Autonomous Driving in Adverse Weather and Lighting
di: Assion, Felix, et al.
Pubblicazione: (2024)

ProtoTTA: Prototype-Guided Test-Time Adaptation
di: Abootorabi, Mohammad Mahdi, et al.
Pubblicazione: (2026)

ICPR 2024 Competition on Safe Segmentation of Drive Scenes in Unstructured Traffic and Adverse Weather Conditions
di: Shaik, Furqan Ahmed, et al.
Pubblicazione: (2024)

Unraveling Batch Normalization for Realistic Test-Time Adaptation
di: Su, Zixian, et al.
Pubblicazione: (2023)

Test Time Adaptation Using Adaptive Quantile Recalibration
di: Mehrbod, Paria, et al.
Pubblicazione: (2025)

STAG: Structural Test-time Alignment of Gradients for Online Adaptation
di: Shin, Juhyeon, et al.
Pubblicazione: (2024)

Diversity-aware Buffer for Coping with Temporally Correlated Data Streams in Online Test-time Adaptation
di: Döbler, Mario, et al.
Pubblicazione: (2024)

MOS: Model Synergy for Test-Time Adaptation on LiDAR-Based 3D Object Detection
di: Chen, Zhuoxiao, et al.
Pubblicazione: (2024)

D-TPT: Dimensional Entropy Maximization for Calibrating Test-Time Prompt Tuning in Vision-Language Models
di: Han, Jisu, et al.
Pubblicazione: (2025)

DPCore: Dynamic Prompt Coreset for Continual Test-Time Adaptation
di: Zhang, Yunbei, et al.
Pubblicazione: (2024)

CLIPArTT: Adaptation of CLIP to New Domains at Test Time
di: Hakim, Gustavo Adolfo Vargas, et al.
Pubblicazione: (2024)

Interpretable Motion-Attentive Maps: Spatio-Temporally Localizing Concepts in Video Diffusion Transformers
di: Jun, Youngjun, et al.
Pubblicazione: (2026)