Papers › CRIS: CLIP-Driven Referring Image Segmentation

CRIS: CLIP-Driven Referring Image Segmentation

30 Nov 2021CVPR 2022 1arXiv:2111.15174archive 2025-07-28

Zhaoqing Wang, Yu Lu, Qiang Li, Xunqiang Tao, Yandong Guo, Mingming Gong, Tongliang Liu

Referring image segmentation aims to segment a referent via a natural linguistic expression.Due to the distinct data properties between text and image, it is challenging for a network to well align text and pixel-level features. Existing approaches use pretrained models to facilitate learning, yet separately transfer the language/vision knowledge from pretrained models, ignoring the multi-modal corresponding information. Inspired by the recent advance in Contrastive Language-Image Pretraining (CLIP), in this paper, we propose an end-to-end CLIP-Driven Referring Image Segmentation framework (CRIS). To transfer the multi-modal knowledge effectively, CRIS resorts to vision-language decoding and contrastive learning for achieving the text-to-pixel alignment. More specifically, we design a vision-language decoder to propagate fine-grained semantic information from textual representations to each pixel-level activation, which promotes consistency between the two modalities. In addition, we present text-to-pixel contrastive learning to explicitly enforce the text feature similar to the related pixel-level features and dissimilar to the irrelevances. The experimental results on three benchmark datasets demonstrate that our proposed framework significantly outperforms the state-of-the-art performance without any post-processing. The code will be released.

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basic_clean DerrickWang005/CRIS.pytorch/utils/simple_tokenizer.py official repository ran · our draft was wrong fingerprinted MIT (permissive) · 98f385d847636a3e · report
conv_layer DerrickWang005/CRIS.pytorch/model/layers.py official repository ran · our draft was wrong MIT (permissive) · dbfe3357dc25ca5f · report
get_pairs DerrickWang005/CRIS.pytorch/utils/simple_tokenizer.py official repository ran · our draft was wrong MIT (permissive) · d919ae32e5e4e616 · report
init_random_seed DerrickWang005/CRIS.pytorch/utils/misc.py official repository ran MIT (permissive) · 539cbfa1328eb51b · report
linear_layer DerrickWang005/CRIS.pytorch/model/layers.py official repository ran MIT (permissive) · 89f9fd49ddec76ba · report
trainMetricGPU DerrickWang005/CRIS.pytorch/utils/misc.py official repository ran MIT (permissive) · 78241a45492d6667 · report
whitespace_clean DerrickWang005/CRIS.pytorch/utils/simple_tokenizer.py official repository ran · our draft was wrong fingerprinted MIT (permissive) · 9542161e9640b858 · report
build_model DerrickWang005/CRIS.pytorch/model/clip.py official repository unverified MIT (permissive) · d761a6dca9831c24 · report
concat_all_gather DerrickWang005/CRIS.pytorch/utils/misc.py official repository unverified MIT (permissive) · 73cecca9f3575f09 · report
load_cfg_from_cfg_file DerrickWang005/CRIS.pytorch/utils/config.py official repository unverified MIT (permissive) · cc23416cff396c39 · report
loads_pyarrow DerrickWang005/CRIS.pytorch/utils/dataset.py official repository unverified MIT (permissive) · b4c154b6f0568b6b · report
merge_cfg_from_list DerrickWang005/CRIS.pytorch/utils/config.py official repository unverified MIT (permissive) · 022883c7911679b3 · report

Tasks

Contrastive LearningDecoderGeneralized Referring Expression SegmentationImage SegmentationReferring Expression SegmentationSegmentationSemantic Segmentation

Results from the paper archive 2025-07-28

TaskDatasetModelMetricValueRank at snapshotLeaderboardReport
Generalized Referring Expression Segmentation gRefCOCO CRIS cIoU 55.34 #10 of 13 Archive leaderboard report
Generalized Referring Expression Segmentation gRefCOCO CRIS gIoU 56.27 #10 of 13 Archive leaderboard report
Referring Expression Segmentation RefCOCO+ test B CRIS Overall IoU 53.68 #20 of 30 Archive leaderboard report
Referring Expression Segmentation RefCOCO+ testA CRIS Overall IoU 68.08 #20 of 30 Archive leaderboard report
Referring Expression Segmentation RefCOCO+ val CRIS Overall IoU 62.27 #22 of 33 Archive leaderboard report
Referring Expression Segmentation RefCoCo val CRIS Overall IoU 70.47 #25 of 37 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

Contrastive Learning

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