Papers › TopoFR: A Closer Look at Topology Alignment on Face Recognition

TopoFR: A Closer Look at Topology Alignment on Face Recognition

14 Oct 2024arXiv:2410.10587archive 2025-07-28

Jun Dan, Yang Liu, Jiankang Deng, Haoyu Xie, Siyuan Li, Baigui Sun, Shan Luo

The field of face recognition (FR) has undergone significant advancements with the rise of deep learning. Recently, the success of unsupervised learning and graph neural networks has demonstrated the effectiveness of data structure information. Considering that the FR task can leverage large-scale training data, which intrinsically contains significant structure information, we aim to investigate how to encode such critical structure information into the latent space. As revealed from our observations, directly aligning the structure information between the input and latent spaces inevitably suffers from an overfitting problem, leading to a structure collapse phenomenon in the latent space. To address this problem, we propose TopoFR, a novel FR model that leverages a topological structure alignment strategy called PTSA and a hard sample mining strategy named SDE. Concretely, PTSA uses persistent homology to align the topological structures of the input and latent spaces, effectively preserving the structure information and improving the generalization performance of FR model. To mitigate the impact of hard samples on the latent space structure, SDE accurately identifies hard samples by automatically computing structure damage score (SDS) for each sample, and directs the model to prioritize optimizing these samples. Experimental results on popular face benchmarks demonstrate the superiority of our TopoFR over the state-of-the-art methods. Code and models are available at: https://github.com/modelscope/facechain/tree/main/face_module/TopoFR.

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PersistentHomologyCalculation modelscope/facechain/face_module/TopoFR/persistent_homology.py official repository ran · metamorphic tier: deterministic fingerprinted Apache-2.0 (permissive) · 97353204a3dd336d · report
TopologicalSignatureDistance modelscope/facechain/face_module/TopoFR/persistent_homology.py official repository ran Apache-2.0 (permissive) · 21848401dad84d15 · report
UnionFind modelscope/facechain/face_module/TopoFR/persistent_homology.py official repository ran · metamorphic tier: deterministic Apache-2.0 (permissive) · 64fde28f43d7eedb · report
compute_distance_matrix modelscope/facechain/face_module/TopoFR/persistent_homology.py official repository ran · our draft was wrong fingerprinted Apache-2.0 (permissive) · b1f7845a6d23b0c3 · report
compute_topological_loss modelscope/facechain/face_module/TopoFR/persistent_homology.py official repository unverified Apache-2.0 (permissive) · a3ac26a1a2a72f40 · report
divideIntoNstrand DanJun6737/TopoFR/eval_ijbc_ms1mv2.py community ran · our draft was wrong fingerprinted no licence file found · pointer only · 2da848988b60d9cc · report
read_template_media_list DanJun6737/TopoFR/eval_ijbc_ms1mv2.py community unverified no licence file found · pointer only · e60885cdbeb940b6 · report
read_template_pair_list DanJun6737/TopoFR/eval_ijbc_ms1mv2.py community unverified no licence file found · pointer only · 897480715a729925 · report
register_corrector identical code first harvested elsewhere ran · our draft was wrong licence of this copy not recorded · a05b1d0cf3f508b4 · report
register_predictor identical code first harvested elsewhere ran · our draft was wrong licence of this copy not recorded · 473066ddf62a075a · report
get_predictor identical code first harvested elsewhere unverified licence of this copy not recorded · a58facb8fe71823a · report

Tasks

Face Recognition

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Methods

ALIGN

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