Cross-Domain Facial Expression Recognition

Description from the archive archive 2025-07-28.

Benchmarks archive 2025-07-28

2 leaderboard tables shown for this task, 2 with rows (a “benchmark” on this site is a table with at least one row, as on /sota), ordered by row count. “Best model” is the first row in the archive's own order at snapshot; nothing is re-ranked here and metric direction is not recorded in the archive. PwC's Trend sparklines are not in the archive, so that column is omitted.

Syntology column: samples harvested from the paper's repositories and executed on synthesized fixtures; “ran” is not a correctness claim and does not order the table. A dash means no Syntology record for that paper, not a recorded non-run. Read from the graph 2026-09-24.

Libraries

Not in the archive: the export carries no per-task library table, so there is nothing to show at snapshot 2025-07-28.

Datasets archive 2025-07-28

No dataset record in the archive lists this task.

Subtasks archive 2025-07-28

No subtask under this task in the archive's task tree.

Parent tasks archive 2025-07-28

Most implemented papers archive 2025-07-28

4 shown of 4 papers with code (4 tagged with this task in all), ordered by repositories listed in the archive, not by stars (the archive holds no stars, so PwC's “Social” and “Latest” sorts cannot be reproduced). Papers without a page here are shown as plain text.

• Adaptive Global-Local Representation Learning and Selection for Cross-Domain Facial Expression Recognition
  20 Jan 2024 1 repository listed
  Specifically, the framework consists of separate global-local adversarial learning modules that learn domain-invariant global and local features independently.
• Cluster-level pseudo-labelling for source-free cross-domain facial expression recognition
  11 Oct 2022 1 repository listed
  Automatically understanding emotions from visual data is a fundamental task for human behaviour understanding.
• Cross-Domain Facial Expression Recognition: A Unified Evaluation Benchmark and Adversarial Graph Learning
  3 Aug 2020 1 repository listed
  Although each declares to achieve superior performance, fair comparisons are lacking due to the inconsistent choices of the source/target datasets and feature extractors.
• Adversarial Graph Representation Adaptation for Cross-Domain Facial Expression Recognition
  3 Aug 2020 1 repository listed
  However, most of these works focus on holistic feature adaptation, and they ignore local features that are more transferable across different datasets.