Papers › CondNet: Conditional Classifier for Scene Segmentation
CondNet: Conditional Classifier for Scene Segmentation
Changqian Yu, Yuanjie Shao, Changxin Gao, Nong Sang
The fully convolutional network (FCN) has achieved tremendous success in dense visual recognition tasks, such as scene segmentation. The last layer of FCN is typically a global classifier (1x1 convolution) to recognize each pixel to a semantic label. We empirically show that this global classifier, ignoring the intra-class distinction, may lead to sub-optimal results. In this work, we present a conditional classifier to replace the traditional global classifier, where the kernels of the classifier are generated dynamically conditioned on the input. The main advantages of the new classifier consist of: (i) it attends on the intra-class distinction, leading to stronger dense recognition capability; (ii) the conditional classifier is simple and flexible to be integrated into almost arbitrary FCN architectures to improve the prediction. Extensive experiments demonstrate that the proposed classifier performs favourably against the traditional classifier on the FCN architecture. The framework equipped with the conditional classifier (called CondNet) achieves new state-of-the-art performances on two datasets. The code and models are available at https://git.io/CondNet.
Code
Repository list and official/mentioned flags are the archive's, frozen 2025-07-28. Reachability, where shown, is from one Syntology probe window (2026-09-16 to 2026-09-18); repositories not probed show nothing. GitHub stars are not tracked.
Code Syntology ran Syntology
Not run by Syntology. Nothing on this page verifies that the listed code works.
Tasks
Results from the paper archive 2025-07-28
| Task | Dataset | Model | Metric | Value | Rank at snapshot | Leaderboard | Report |
|---|---|---|---|---|---|---|---|
| Semantic Segmentation | ADE20K | CondNet(ResNest-101) | Validation mIoU | 47.54 | #162 of 235 | Archive leaderboard | report |
| Semantic Segmentation | ADE20K | CondNet(ResNet-101) | Validation mIoU | 47.38 | #164 of 235 | Archive leaderboard | report |
| Semantic Segmentation | PASCAL Context | CondNet(ResNest-101) | mIoU | 57 | #21 of 66 | Archive leaderboard | report |
| Semantic Segmentation | PASCAL Context | CondNet(ResNet-101) | mIoU | 56.0 | #26 of 66 | Archive leaderboard | report |
Ranks are positions in the archive's leaderboards as they stood at the 2025-07-28 snapshot. Results published since then are not among these rows, so a rank here is not a current standing.
Methods
Report a problem or propose a change · a person checks every report against the paper or source before anything changes; decisions are listed on /corrections