Semi-Supervised Interior Decoration Style Classification with Contrastive Mutual Learning
Abstract
:1. Introduction
- We propose a novel PCML framework to facilitate semi-supervised interior decoration style classification by exploiting the diversified pseudo-labels generated by distinct subnetworks.
- PCML integrates two novel modules: ICR regularization to direct the subnetworks review the labeled imaged with inconsistent predictions, and CCL regularization to learn discriminative feature representations of unlabeled images.
- The synergistic learning among the distinct subnetworks, ICR regularization, and CCL regularization helps the model overcome confirmation bias. Extensive experimental results demonstrate the superiority of PCML.
2. Related Works
2.1. Semi-Supervised Learning
2.2. Contrastive Learning
3. Pseudo-Label-Guided Contrastive Mutual Learning Framework
3.1. Architecture Overview
3.2. Inconsistency-Aware Relearning
3.3. Class-Aware Contrastive Learning
3.4. Objective Function
Algorithm 1: Optimization of PCML Framework |
4. Experiments
4.1. Datasets and Pre-Processing
4.2. Experimental Setup
4.3. Comparison with State-of-the-Art Methods
4.4. Analysis of the Proposed PCML Framework
4.4.1. Efficacy of Different Components
4.4.2. Impact of Hyper-Parameters
4.4.3. Impact of Input Noise
5. Conclusions
Author Contributions
Funding
Data Availability Statement
Conflicts of Interest
Abbreviations
PCML | pseudo-label-guided contrastive mutual learning |
ICR | inconsistency-aware relearning |
CCL | class-aware contrastive learning |
SSL | semi-supervised learning |
MT | mean teacher |
Grad-CAM | Gradient Weighted Class Activation Mapping |
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Methods | Percentage | Metrics | ||||||
---|---|---|---|---|---|---|---|---|
Labeled | Unlabeled | AUC (%)↑ | ACC (%)↑ | SEN (%)↑ | SPE (%)↑ | PREC (%)↑ | F1 (%)↑ | |
DenseNet [45] | 100% | 0 | 97.44 | 94.04 | 86.12 | 95.09 | 86.18 | 86.08 |
ResNet [44] | 100% | 0 | 97.30 | 93.73 | 85.47 | 95.30 | 83.55 | 84.23 |
DenseNet [45] | 20% | 0 | 93.76 | 88.53 | 73.84 | 91.45 | 72.73 | 72.90 |
ResNet [44] | 20% | 0 | 93.31 | 89.30 | 76.39 | 91.22 | 75.50 | 75.58 |
MixMatch [26] | 20% | 80% | 94.77 (1.01) | 90.83 (2.29) | 78.98 (5.14) | 91.81 (0.36) | 80.85 (8.12) | 79.48 (6.58) |
ReMixMatch [46] | 20% | 80% | 95.48 (1.72) | 90.52 (1.99) | 76.11 (2.27) | 92.10 (0.65) | 80.42 (7.69) | 77.55 (4.65) |
CoMatch [41] | 20% | 80% | 95.43 (1.67) | 91.28 (2.75) | 78.67 (4.48) | 92.53 (1.08) | 82.05 (9.32) | 79.85 (6.95) |
FixMatch [27] | 20% | 80% | 95.29 (1.53) | 89.76 (1.22) | 77.26 (3.42) | 91.81 (0.36) | 77.19 (4.46) | 76.90 (4.00) |
MT [15] | 20% | 80% | 95.55 (1.79) | 90.06 (1.53) | 74.03 (0.20) | 91.51 (0.06) | 81.07 (8.34) | 75.98 (3.08) |
SRC-MT [22] | 20% | 80% | 95.84 (2.08) | 91.36 (2.83) | 80.11 (6.27) | 93.08 (1.63) | 81.33 (8.60) | 79.76 (6.86) |
PCML (Ours) | 20% | 80% | 96.82 (3.06) | 93.58 (5.05) | 84.12 (10.3) | 94.48 (3.03) | 87.27 (14.5) | 85.36 (12.5) |
Methods | Percentage | Metrics | ||||||
---|---|---|---|---|---|---|---|---|
Labeled | Unlabeled | AUC (%)↑ | ACC (%)↑ | SEN (%)↑ | SPE (%)↑ | PREC (%)↑ | F1 (%)↑ | |
DenseNet [45] | 100% | 0 | 99.61 | 97.28 | 95.58 | 97.91 | 93.85 | 94.61 |
ResNet [44] | 100% | 0 | 99.33 | 96.11 | 92.39 | 97.11 | 92.37 | 92.34 |
DenseNet [45] | 20% | 0 | 93.96 | 87.69 | 78.75 | 91.09 | 77.72 | 76.53 |
ResNet [44] | 20% | 0 | 93.71 | 86.92 | 75.01 | 90.37 | 75.97 | 73.51 |
MixMatch [26] | 20% | 80% | 95.75 (1.79) | 91.58 (3.89) | 84.72 (5.97) | 93.55 (2.47) | 83.14 (5.42) | 83.63 (7.10) |
ReMixMatch [46] | 20% | 80% | 96.51 (2.55) | 92.10 (4.40) | 86.13 (7.37) | 93.86 (2.78) | 85.22 (7.50) | 85.03 (8.50) |
CoMatch [41] | 20% | 80% | 97.57 (3.61) | 92.75 (5.05) | 86.55 (7.80) | 94.42 (3.33) | 85.90 (8.18) | 85.85 (9.32) |
FixMatch [27] | 20% | 80% | 97.66 (3.70) | 93.39 (5.70) | 86.86 (8.10) | 95.07 (3.98) | 85.54 (7.82) | 86.11 (9.58) |
MT [15] | 20% | 80% | 96.38 (2.42) | 92.75 (5.05) | 87.45 (8.70) | 94.55 (3.46) | 86.38 (8.66) | 86.70 (10.2) |
SRC-MT [22] | 20% | 80% | 97.35 (3.39) | 92.49 (4.79) | 88.66 (9.91) | 94.42 (3.33) | 84.50 (6.77) | 84.07 (7.54) |
PCML (Ours) | 20% | 80% | 98.25 (4.29) | 95.21 (7.51) | 90.88 (12.1) | 96.65 (5.56) | 90.47 (12.8) | 90.55 (14.0) |
Methods | Percentage | Metrics | ||||||
---|---|---|---|---|---|---|---|---|
Labeled | Unlabeled | AUC (%)↑ | ACC (%)↑ | SEN (%)↑ | SPE (%)↑ | PREC (%)↑ | F1 (%)↑ | |
DenseNet [45] | 100% | 0 | 94.31 | 92.42 | 83.30 | 94.26 | 83.91 | 83.52 |
ResNet [44] | 100% | 0 | 94.86 | 92.09 | 81.81 | 93.90 | 84.50 | 82.52 |
DenseNet [45] | 20% | 0 | 89.74 | 86.95 | 69.34 | 89.78 | 69.45 | 67.28 |
ResNet [44] | 20% | 0 | 91.06 | 87.88 | 70.41 | 90.89 | 68.94 | 67.81 |
MixMatch [26] | 20% | 80% | 91.26 (1.53) | 88.89 (1.94) | 72.91 (3.57) | 91.63 (1.85) | 77.07 (7.62) | 73.36 (6.07) |
ReMixMatch [46] | 20% | 80% | 92.12 (2.38) | 89.39 (2.44) | 72.91 (3.57) | 92.19 (2.41) | 74.09 (4.64) | 75.81 (8.53) |
CoMatch [41] | 20% | 80% | 91.58 (1.84) | 89.65 (2.69) | 74.69 (5.36) | 92.17 (2.38) | 77.54 (8.08) | 74.06 (6.77) |
FixMatch [27] | 20% | 80% | 92.53 (2.80) | 88.72 (1.77) | 70.55 (1.21) | 91.63 (1.85) | 76.60 (7.15) | 69.57 (2.29) |
MT [15] | 20% | 80% | 91.91 (2.17) | 87.96 (1.01) | 71.77 (2.44) | 91.16 (1.38) | 73.74 (4.29) | 69.70 (2.42) |
SRC-MT [22] | 20% | 80% | 92.41 (2.67) | 88.22 (1.26) | 71.98 (2.64) | 91.07 (1.29) | 74.23 (4.78) | 70.43 (3.15) |
PCML (Ours) | 20% | 80% | 93.92 (4.19) | 91.25 (4.29) | 77.27 (7.93) | 93.33 (3.55) | 79.74 (10.3) | 76.74 (9.46) |
Methods | Percentage | Metrics | ||||||
---|---|---|---|---|---|---|---|---|
Labeled | Unlabeled | AUC (%)↑ | ACC (%)↑ | SEN (%)↑ | SPE (%)↑ | PREC (%)↑ | F1 (%)↑ | |
DenseNet [45] | 100% | 0 | 98.03 | 94.71 | 91.66 | 95.67 | 89.27 | 90.2 |
ResNet [44] | 100% | 0 | 97.87 | 93.75 | 89.48 | 95.12 | 86.94 | 88.06 |
DenseNet [45] | 20% | 0 | 91.89 | 87.26 | 76.37 | 89.71 | 74.64 | 75.24 |
ResNet [44] | 20% | 0 | 91.29 | 83.89 | 72.65 | 87.08 | 68.83 | 69.04 |
MixMatch [26] | 20% | 80% | 95.20 (3.31) | 89.18 (1.92) | 79.68 (3.31) | 90.46 (0.75) | 80.20 (5.55) | 78.60 (3.37) |
ReMixMatch [46] | 20% | 80% | 95.89 (4.00) | 91.11 (3.85) | 82.60 (6.23) | 92.82 (3.11) | 78.12 (3.48) | 80.27 (5.03) |
CoMatch [41] | 20% | 80% | 96.08 (4.18) | 89.66 (2.40) | 82.20 (5.83) | 91.93 (2.22) | 75.89 (1.24) | 76.62 (1.38) |
FixMatch [27] | 20% | 80% | 94.93 (3.04) | 89.90 (2.64) | 83.21 (6.85) | 91.74 (2.03) | 82.01 (7.36) | 81.72 (6.48) |
MT [15] | 20% | 80% | 93.97 (2.08) | 88.46 (1.20) | 81.76 (5.39) | 91.92 (2.21) | 76.00 (1.36) | 77.65 (2.41) |
SRC-MT [22] | 20% | 80% | 95.45 (3.56) | 91.11 (3.85) | 85.17 (8.80) | 94.09 (4.39) | 77.86 (3.22) | 79.53 (4.29) |
PCML (Ours) | 20% | 80% | 97.23 (5.34) | 93.51 (6.25) | 88.96 (12.6) | 94.75 (5.05) | 86.35 (11.7) | 87.59 (12.4) |
Methods | Percentage | Metrics | ||||||
---|---|---|---|---|---|---|---|---|
Labeled | Unlabeled | AUC (%)↑ | ACC (%)↑ | SEN (%)↑ | SPE (%)↑ | PREC (%)↑ | F1 (%)↑ | |
DenseNet [45] | 100% | 0 | 88.40 | 85.74 | 72.55 | 89.59 | 72.35 | 71.95 |
ResNet [44] | 100% | 0 | 88.57 | 85.16 | 72.58 | 89.03 | 71.12 | 70.68 |
DenseNet [45] | 20% | 0 | 81.35 | 78.71 | 57.78 | 84.75 | 59.35 | 56.82 |
ResNet [44] | 20% | 0 | 82.45 | 78.32 | 57.60 | 84.86 | 61.64 | 56.12 |
MixMatch [26] | 20% | 80% | 84.04 (2.69) | 81.84 (3.13) | 65.42 (7.64) | 86.67 (1.92) | 63.59 (4.24) | 64.01 (7.20) |
ReMixMatch [46] | 20% | 80% | 85.23 (3.88) | 81.25 (2.54) | 63.51 (5.74) | 86.34 (1.58) | 62.17 (2.82) | 62.11 (5.30) |
CoMatch [41] | 20% | 80% | 85.20 (3.85) | 80.86 (2.15) | 65.62 (7.84) | 86.32 (1.56) | 62.25 (2.90) | 62.25 (5.43) |
FixMatch [27] | 20% | 80% | 84.96 (3.61) | 81.45 (2.73) | 67.54 (9.77) | 86.34 (1.58) | 63.89 (4.54) | 63.97 (7.16) |
MT [15] | 20% | 80% | 84.44 (3.09) | 80.86 (2.15) | 64.05 (6.27) | 86.67 (1.92) | 61.37 (2.02) | 61.67 (4.86) |
SRC-MT [22] | 20% | 80% | 86.01 (4.66) | 80.08 (1.37) | 60.23 (2.46) | 86.60 (1.84) | 61.64 (2.29) | 60.04 (3.23) |
PCML (Ours) | 20% | 80% | 86.71 (5.36) | 82.42 (3.71) | 69.26 (11.5) | 86.80 (2.05) | 65.10 (5.75) | 66.52 (9.71) |
ResNet | DenseNet | CPS | ICR | CCL | TV Background Wall Dataset | |||||
---|---|---|---|---|---|---|---|---|---|---|
AUC (%)↑ | ACC (%)↑ | SEN (%)↑ | SPE (%)↑ | PREC (%)↑ | F1 (%)↑ | |||||
✓ | 93.31 | 89.30 | 76.39 | 91.22 | 75.50 | 75.58 | ||||
✓ | 93.76 | 88.53 | 73.84 | 91.45 | 72.73 | 72.90 | ||||
✓ | ✓ | ✓ | 96.17 | 91.44 | 79.42 | 93.00 | 81.84 | 79.52 | ||
✓ | ✓ | ✓ | ✓ | 96.40 | 92.28 | 83.15 | 93.29 | 81.94 | 82.40 | |
✓ | ✓ | ✓ | ✓ | ✓ | 96.82 | 93.58 | 84.12 | 94.48 | 87.27 | 85.36 |
ResNet | DenseNet | CPS | ICR | CCL | TV Background Wall Dataset | |||||
---|---|---|---|---|---|---|---|---|---|---|
AUC (%)↑ | ACC (%)↑ | SEN (%)↑ | SPE (%)↑ | PREC (%)↑ | F1 (%)↑ | |||||
✓ | 91.06 | 87.88 | 70.41 | 90.89 | 68.94 | 67.81 | ||||
✓ | 89.74 | 86.95 | 69.34 | 89.78 | 69.45 | 67.28 | ||||
✓ | ✓ | ✓ | 92.35 | 88.97 | 70.71 | 91.88 | 78.68 | 68.26 | ||
✓ | ✓ | ✓ | ✓ | 93.91 | 88.64 | 72.41 | 90.90 | 79.50 | 72.33 | |
✓ | ✓ | ✓ | ✓ | ✓ | 93.92 | 91.25 | 77.27 | 93.33 | 79.74 | 76.74 |
Metrics | ||||||
AUC | ACC | SEN | SPE | PREC | F1 | |
96.24 | 91.28 | 78.46 | 92.58 | 82.79 | 79.37 | |
96.12 | 91.97 | 82.01 | 92.58 | 82.55 | 81.71 | |
96.50 | 91.97 | 80.21 | 92.89 | 84.75 | 81.86 | |
96.82 | 93.58 | 84.12 | 94.48 | 87.27 | 85.36 | |
96.51 | 91.67 | 81.17 | 93.00 | 82.19 | 80.74 | |
Metrics | ||||||
AUC | ACC | SEN | SPE | PREC | F1 | |
95.31 | 90.37 | 78.91 | 91.62 | 78.53 | 78.23 | |
95.59 | 91.67 | 81.53 | 92.18 | 82.20 | 81.46 | |
96.50 | 92.81 | 82.24 | 93.88 | 84.80 | 82.79 | |
96.82 | 93.58 | 84.12 | 94.48 | 87.27 | 85.36 | |
95.94 | 92.97 | 82.06 | 94.44 | 83.84 | 82.34 | |
Metrics | ||||||
AUC | ACC | SEN | SPE | PREC | F1 | |
96.30 | 92.28 | 80.61 | 93.18 | 85.32 | 82.11 | |
96.82 | 93.58 | 84.12 | 94.48 | 87.27 | 85.36 | |
96.51 | 92.58 | 82.24 | 93.87 | 82.91 | 82.26 | |
95.23 | 91.82 | 81.19 | 93.70 | 81.03 | 80.61 | |
94.95 | 90.67 | 79.40 | 92.97 | 78.49 | 78.05 |
Settings | TV Background Wall | |||||
AUC | ACC | SEN | SPE | PREC | F1 | |
1 | 96.82 | 93.58 | 84.12 | 94.48 | 87.27 | 85.36 |
2 | 96.24 | 92.13 | 80.82 | 93.47 | 82.63 | 81.02 |
3 | 96.09 | 91.67 | 81.93 | 93.26 | 80.11 | 80.64 |
Settings | Chandelier | |||||
AUC | ACC | SEN | SPE | PREC | F1 | |
1 | 98.25 | 95.21 | 90.88 | 96.65 | 90.47 | 90.55 |
2 | 97.96 | 94.43 | 89.38 | 96.29 | 89.63 | 89.11 |
3 | 98.90 | 95.47 | 91.73 | 96.71 | 90.16 | 90.78 |
Settings | Living Room | |||||
AUC | ACC | SEN | SPE | PREC | F1 | |
1 | 93.92 | 91.25 | 77.27 | 93.33 | 79.74 | 76.74 |
2 | 93.34 | 90.91 | 78.47 | 93.03 | 79.02 | 77.58 |
3 | 93.16 | 91.25 | 79.19 | 93.12 | 79.07 | 78.26 |
Settings | Dining Room | |||||
AUC | ACC | SEN | SPE | PREC | F1 | |
1 | 97.23 | 93.51 | 88.96 | 94.75 | 86.35 | 87.59 |
2 | 97.84 | 94.71 | 88.08 | 95.46 | 89.71 | 88.68 |
3 | 98.15 | 93.99 | 85.16 | 94.30 | 87.59 | 85.86 |
Settings | Bedroom | |||||
AUC | ACC | SEN | SPE | PREC | F1 | |
1 | 86.71 | 82.42 | 69.26 | 86.80 | 65.10 | 66.52 |
2 | 87.68 | 82.03 | 67.81 | 87.7 | 70.43 | 63.14 |
3 | 88.32 | 82.23 | 68.81 | 86.98 | 70.58 | 64.37 |
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Guo, L.; Zeng, H.; Shi, X.; Xu, Q.; Shi, J.; Bai, K.; Liang, S.; Hang, W. Semi-Supervised Interior Decoration Style Classification with Contrastive Mutual Learning. Mathematics 2024, 12, 2980. https://doi.org/10.3390/math12192980
Guo L, Zeng H, Shi X, Xu Q, Shi J, Bai K, Liang S, Hang W. Semi-Supervised Interior Decoration Style Classification with Contrastive Mutual Learning. Mathematics. 2024; 12(19):2980. https://doi.org/10.3390/math12192980
Chicago/Turabian StyleGuo, Lichun, Hao Zeng, Xun Shi, Qing Xu, Jinhui Shi, Kui Bai, Shuang Liang, and Wenlong Hang. 2024. "Semi-Supervised Interior Decoration Style Classification with Contrastive Mutual Learning" Mathematics 12, no. 19: 2980. https://doi.org/10.3390/math12192980
APA StyleGuo, L., Zeng, H., Shi, X., Xu, Q., Shi, J., Bai, K., Liang, S., & Hang, W. (2024). Semi-Supervised Interior Decoration Style Classification with Contrastive Mutual Learning. Mathematics, 12(19), 2980. https://doi.org/10.3390/math12192980