1 code implementation • 5 Feb 2024 • Haoxiang Wang, Haozhe Si, Huajie Shao, Han Zhao
To delve into the CG challenge, we develop CG-Bench, a suite of CG benchmarks derived from existing real-world image datasets, and observe that the prevalent pretraining-finetuning paradigm on foundational models, such as CLIP and DINOv2, struggles with the challenge.
1 code implementation • 2 Nov 2023 • Haoxiang Wang, Gargi Balasubramaniam, Haozhe Si, Bo Li, Han Zhao
First, in the binary classification setup of Rosenfeld et al. (2021), we show that our first algorithm, ISR-Mean, can identify the subspace spanned by invariant features from the first-order moments of the class-conditional distributions, and achieve provable domain generalization with $d_s+1$ training environments.
1 code implementation • CVPR 2023 • Haozhe Si, Bin Zhao, Dong Wang, Yunpeng Gao, Mulin Chen, Zhigang Wang, Xuelong Li
We show that our framework circumvents the needs for the depth and AIF image ground-truth, and receives superior predictions, thus closing the gap between the theoretical success of DFD works and their applications in the real world.
1 code implementation • 30 Jan 2022 • Haoxiang Wang, Haozhe Si, Bo Li, Han Zhao
Our first algorithm, ISR-Mean, can identify the subspace spanned by invariant features from the first-order moments of the class-conditional distributions, and achieve provable domain generalization with $d_s+1$ training environments under the data model of Rosenfeld et al. (2021).