The Right Inference Strategy Is All You Need: Nearly Training-Free Domain-Wise Inference for EgoCross Challenge
Fuente:
arXiv
Saved in:
| Main Authors: | Wu, Leyi, Zhao, Yifan, Zhang, Jinjie, Li, Yinchuan, Chen, Ying-Cong |
|---|---|
| Format: | Preprint |
| Published: |
2026
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
OmniEgo-R$^2$: A Routed Reasoning Framework for the 1st Cross-Domain EgoCross Challenge at CVPR 2026
by: Li, Zixu, et al.
Published: (2026)
by: Li, Zixu, et al.
Published: (2026)
EgoCross: Benchmarking Multimodal Large Language Models for Cross-Domain Egocentric Video Question Answering
by: Li, Yanjun, et al.
Published: (2025)
by: Li, Yanjun, et al.
Published: (2025)
Is Ego Status All You Need for Open-Loop End-to-End Autonomous Driving?
by: Li, Zhiqi, et al.
Published: (2023)
by: Li, Zhiqi, et al.
Published: (2023)
RoboStressBench: Benchmarking VLM Robustness to Physical Visual Stress in Embodied Scenes
by: Wu, Leyi, et al.
Published: (2026)
by: Wu, Leyi, et al.
Published: (2026)
Alignment is All You Need: A Training-free Augmentation Strategy for Pose-guided Video Generation
by: Jin, Xiaoyu, et al.
Published: (2024)
by: Jin, Xiaoyu, et al.
Published: (2024)
Transferable-guided Attention Is All You Need for Video Domain Adaptation
by: Sacilotti, André, et al.
Published: (2024)
by: Sacilotti, André, et al.
Published: (2024)
ParameterNet: Parameters Are All You Need
by: Han, Kai, et al.
Published: (2023)
by: Han, Kai, et al.
Published: (2023)
All You Need to Know About Training Image Retrieval Models
by: Berton, Gabriele, et al.
Published: (2025)
by: Berton, Gabriele, et al.
Published: (2025)
Memory augment is All You Need for image restoration
by: Zhang, Xiao Feng, et al.
Published: (2023)
by: Zhang, Xiao Feng, et al.
Published: (2023)
Pairwise Comparisons Are All You Need
by: Chahine, Nicolas, et al.
Published: (2024)
by: Chahine, Nicolas, et al.
Published: (2024)
Free Lunch to Meet the Gap: Intermediate Domain Reconstruction for Cross-Domain Few-Shot Learning
by: Zhang, Tong, et al.
Published: (2025)
by: Zhang, Tong, et al.
Published: (2025)
[MASK] is All You Need
by: Hu, Vincent Tao, et al.
Published: (2024)
by: Hu, Vincent Tao, et al.
Published: (2024)
Boosting Domain Incremental Learning: Selecting the Optimal Parameters is All You Need
by: Wang, Qiang, et al.
Published: (2025)
by: Wang, Qiang, et al.
Published: (2025)
Ideal Registration? Segmentation is All You Need
by: Chen, Xiang, et al.
Published: (2025)
by: Chen, Xiang, et al.
Published: (2025)
Emu3: Next-Token Prediction is All You Need
by: Wang, Xinlong, et al.
Published: (2024)
by: Wang, Xinlong, et al.
Published: (2024)
IP-Adapter Is All You Need: Towards Fine-Tuning-Free Diffusion-Based Talking Face Generation
by: Wu, Hao, et al.
Published: (2026)
by: Wu, Hao, et al.
Published: (2026)
FreeUV: Ground-Truth-Free Realistic Facial UV Texture Recovery via Cross-Assembly Inference Strategy
by: Yang, Xingchao, et al.
Published: (2025)
by: Yang, Xingchao, et al.
Published: (2025)
Accelerating Inference of Networks in the Frequency Domain
by: Zhao, Chenqiu, et al.
Published: (2024)
by: Zhao, Chenqiu, et al.
Published: (2024)
Zoom and Shift are All You Need
by: Qin, Jiahao
Published: (2024)
by: Qin, Jiahao
Published: (2024)
Reasoning is All You Need for Video Generalization: A Counterfactual Benchmark with Sub-question Evaluation
by: Zhou, Qiji, et al.
Published: (2025)
by: Zhou, Qiji, et al.
Published: (2025)
Is Discretization Fusion All You Need for Collaborative Perception?
by: Yang, Kang, et al.
Published: (2025)
by: Yang, Kang, et al.
Published: (2025)
Attention Is All You Need For Mixture-of-Depths Routing
by: Gadhikar, Advait, et al.
Published: (2024)
by: Gadhikar, Advait, et al.
Published: (2024)
CORDIC Is All You Need
by: Kokane, Omkar, et al.
Published: (2025)
by: Kokane, Omkar, et al.
Published: (2025)
Cross-Validation Is All You Need: A Statistical Approach To Label Noise Estimation
by: Chen, Jianan, et al.
Published: (2023)
by: Chen, Jianan, et al.
Published: (2023)
Image is All You Need to Empower Large-scale Diffusion Models for In-Domain Generation
by: Cao, Pu, et al.
Published: (2023)
by: Cao, Pu, et al.
Published: (2023)
Training for Identity, Inference for Controllability: A Unified Approach to Tuning-Free Face Personalization
by: Pang, Lianyu, et al.
Published: (2025)
by: Pang, Lianyu, et al.
Published: (2025)
All You Need in Knowledge Distillation Is a Tailored Coordinate System
by: Zhou, Junjie, et al.
Published: (2024)
by: Zhou, Junjie, et al.
Published: (2024)
Camera Agnostic Two-Head Network for Ego-Lane Inference
by: Song, Chaehyeon, et al.
Published: (2024)
by: Song, Chaehyeon, et al.
Published: (2024)
Source-Free Domain Adaptation by Optimizing Batch-Wise Cosine Similarity
by: Pathak, Harsharaj, et al.
Published: (2026)
by: Pathak, Harsharaj, et al.
Published: (2026)
Performance is not All You Need: Sustainability Considerations for Algorithms
by: Li, Xiang, et al.
Published: (2025)
by: Li, Xiang, et al.
Published: (2025)
Unsupervised Real-World Denoising: Sparsity is All You Need
by: Chihaoui, Hamadi, et al.
Published: (2025)
by: Chihaoui, Hamadi, et al.
Published: (2025)
Search is All You Need for Few-shot Anomaly Detection
by: Wang, Qishan, et al.
Published: (2025)
by: Wang, Qishan, et al.
Published: (2025)
Exchange Is All You Need for Remote Sensing Change Detection
by: Dong, Sijun, et al.
Published: (2026)
by: Dong, Sijun, et al.
Published: (2026)
Moving Object Segmentation: All You Need Is SAM (and Flow)
by: Xie, Junyu, et al.
Published: (2024)
by: Xie, Junyu, et al.
Published: (2024)
Positive Label Is All You Need for Multi-Label Classification
by: Yuan, Zhixiang, et al.
Published: (2023)
by: Yuan, Zhixiang, et al.
Published: (2023)
Training-Free Action Recognition and Goal Inference with Dynamic Frame Selection
by: Keat, Ee Yeo, et al.
Published: (2024)
by: Keat, Ee Yeo, et al.
Published: (2024)
Annotations Are Not All You Need: A Cross-modal Knowledge Transfer Network for Unsupervised Temporal Sentence Grounding
by: Fang, Xiang, et al.
Published: (2026)
by: Fang, Xiang, et al.
Published: (2026)
3D Prior is All You Need: Cross-Task Few-shot 2D Gaze Estimation
by: Cheng, Yihua, et al.
Published: (2025)
by: Cheng, Yihua, et al.
Published: (2025)
Revisiting Class-Incremental Learning with Pre-Trained Models: Generalizability and Adaptivity are All You Need
by: Zhou, Da-Wei, et al.
Published: (2023)
by: Zhou, Da-Wei, et al.
Published: (2023)
GrootVL: Tree Topology is All You Need in State Space Model
by: Xiao, Yicheng, et al.
Published: (2024)
by: Xiao, Yicheng, et al.
Published: (2024)
Similar Items
-
OmniEgo-R$^2$: A Routed Reasoning Framework for the 1st Cross-Domain EgoCross Challenge at CVPR 2026
by: Li, Zixu, et al.
Published: (2026) -
EgoCross: Benchmarking Multimodal Large Language Models for Cross-Domain Egocentric Video Question Answering
by: Li, Yanjun, et al.
Published: (2025) -
Is Ego Status All You Need for Open-Loop End-to-End Autonomous Driving?
by: Li, Zhiqi, et al.
Published: (2023) -
RoboStressBench: Benchmarking VLM Robustness to Physical Visual Stress in Embodied Scenes
by: Wu, Leyi, et al.
Published: (2026) -
Alignment is All You Need: A Training-free Augmentation Strategy for Pose-guided Video Generation
by: Jin, Xiaoyu, et al.
Published: (2024)