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cs.CV2025

Towards Training-Free Open-World Classification with 3D Generative Models

Xinzhe Xia, Weiguang Zhao, Yuyao Yan +4

3D open-world classification is a challenging yet essential task in dynamic and unstructured real-world scenarios, requiring both open-category and open-pose recognition. To addres…

cs.CV2024

From 2D Images to 3D Model:Weakly Supervised Multi-View Face Reconstruction with Deep Fusion

Weiguang Zhao, Chaolong Yang, Jianan Ye +6

While weakly supervised multi-view face reconstruction (MVR) is garnering increased attention, one critical issue still remains open: how to effectively interact and fuse multiple…

cs.CV2024

Revisiting Mutual Information Maximization for Generalized Category Discovery

Zhaorui Tan, Chengrui Zhang, Xi Yang +2

Generalized category discovery presents a challenge in a realistic scenario, which requires the model's generalization ability to recognize unlabeled samples from known and unknown…

cs.CV2024

SCMix: Stochastic Compound Mixing for Open Compound Domain Adaptation in Semantic Segmentation

Kai Yao, Zhaorui Tan, Zixian Su +3

Open compound domain adaptation (OCDA) aims to transfer knowledge from a labeled source domain to a mix of unlabeled homogeneous compound target domains while generalizing to open…

cs.CV2024

Unraveling Batch Normalization for Realistic Test-Time Adaptation

Zixian Su, Jingwei Guo, Kai Yao +3

While recent test-time adaptations exhibit efficacy by adjusting batch normalization to narrow domain disparities, their effectiveness diminishes with realistic mini-batches due to…