Papers › Revisiting Counterfactual Problems in Referring Expression Comprehension
Revisiting Counterfactual Problems in Referring Expression Comprehension
Zhihan Yu, Ruifan Li
Traditional referring expression comprehension (REC) aims to locate the target referent in an image guided by a text query. Several previous methods have studied on the Counterfactual problem in REC (C-REC) where the objects for a given query cannot be found in the image. However these methods focus on the overall image-text or specific attribute mismatch only. In this paper we address the C-REC problem from a deep perspective of fine-grained attributes. To this aim we first propose a fine-grained counterfactual sample generation method to construct C-REC datasets. Specifically we leverage pre-trained language model such as BERT to modify the attribute words in the queries obtaining the corresponding counterfactual samples. Furthermore we propose a C-REC framework. We first adopt three encoders to extract image text and attribute features. Then our dual-branch attentive fusion module fuses these cross-modal features with two branches by an attention mechanism. At last two prediction heads generate a bounding box and a counterfactual label respectively. In addition we incorporate contrastive learning with the generated counterfactual samples as negatives to enhance the counterfactual perception. Extensive experiments show that our framework achieves promising performance on both public REC datasets RefCOCO/+/g and our constructed C-REC datasets C-RefCOCO/+/g. The code and data are available at https://github.com/Glacier0012/CREC.
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
1 archive task tag without a task page not shown.
Results from the paper archive 2025-07-28
No leaderboard rows for this paper in the archive.
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