Papers › Generalized Decoding for Pixel, Image, and Language

Generalized Decoding for Pixel, Image, and Language

21 Dec 2022CVPR 2023 1arXiv:2212.11270archive 2025-07-28

Xueyan Zou, Zi-Yi Dou, Jianwei Yang, Zhe Gan, Linjie Li, Chunyuan Li, Xiyang Dai, Harkirat Behl, JianFeng Wang, Lu Yuan, Nanyun Peng, Lijuan Wang, Yong Jae Lee, Jianfeng Gao

We present X-Decoder, a generalized decoding model that can predict pixel-level segmentation and language tokens seamlessly. X-Decodert takes as input two types of queries: (i) generic non-semantic queries and (ii) semantic queries induced from text inputs, to decode different pixel-level and token-level outputs in the same semantic space. With such a novel design, X-Decoder is the first work that provides a unified way to support all types of image segmentation and a variety of vision-language (VL) tasks. Further, our design enables seamless interactions across tasks at different granularities and brings mutual benefits by learning a common and rich pixel-level visual-semantic understanding space, without any pseudo-labeling. After pretraining on a mixed set of a limited amount of segmentation data and millions of image-text pairs, X-Decoder exhibits strong transferability to a wide range of downstream tasks in both zero-shot and finetuning settings. Notably, it achieves (1) state-of-the-art results on open-vocabulary segmentation and referring segmentation on eight datasets; (2) better or competitive finetuned performance to other generalist and specialist models on segmentation and VL tasks; and (3) flexibility for efficient finetuning and novel task composition (e.g., referring captioning and image editing). Code, demo, video, and visualization are available at https://x-decoder-vl.github.io.

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Code

microsoft/X-Decoder officialmentioned on GitHubpytorchApache-2.0 report

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Tasks

DecoderImage SegmentationInstance SegmentationPanoptic SegmentationReferring Expression SegmentationSegmentationSemantic SegmentationZero Shot Segmentation

Datasets

Introduced by this paper, per the archive.

Segmentation in the Wild

Results from the paper archive 2025-07-28

TaskDatasetModelMetricValueRank at snapshotLeaderboardReport
Instance Segmentation ADE20K val X-Decoder (Davit-d5, Deform, single-scale, 1280x1280) AP 38.7 #5 of 14 Archive leaderboard report
Instance Segmentation ADE20K val X-Decoder (Davit-d5, Deform, single-scale, 1280x1280) APL 59.6 #5 of 14 Archive leaderboard report
Instance Segmentation ADE20K val X-Decoder (Davit-d5, Deform, single-scale, 1280x1280) APM 43.3 #5 of 14 Archive leaderboard report
Instance Segmentation ADE20K val X-Decoder (Davit-d5, Deform, single-scale, 1280x1280) APS 18.9 #5 of 14 Archive leaderboard report
Instance Segmentation ADE20K val X-Decoder (L) AP 35.8 #9 of 14 Archive leaderboard report
Panoptic Segmentation ADE20K val X-Decoder (Davit-d5, Deform, single-scale, 1280x1280) AP 38.7 #6 of 25 Archive leaderboard report
Panoptic Segmentation ADE20K val X-Decoder (Davit-d5, Deform, single-scale, 1280x1280) PQ 52.4 #6 of 25 Archive leaderboard report
Panoptic Segmentation ADE20K val X-Decoder (Davit-d5, Deform, single-scale, 1280x1280) mIoU 59.1 #6 of 25 Archive leaderboard report
Panoptic Segmentation ADE20K val X-Decoder (L) AP 35.8 #15 of 25 Archive leaderboard report
Panoptic Segmentation ADE20K val X-Decoder (L) PQ 49.6 #15 of 25 Archive leaderboard report
Panoptic Segmentation ADE20K val X-Decoder (L) mIoU 58.1 #15 of 25 Archive leaderboard report
Referring Expression Segmentation RefCOCOg-val X-Decoder (Davit-d5) Overall IoU 64.6 #17 of 23 Archive leaderboard report
Zero Shot Segmentation Segmentation in the Wild SGinW_Team (X-Decoder-L) Mean AP 32.2 #9 of 12 Archive leaderboard report
Zero Shot Segmentation Segmentation in the Wild SGinW_Team (X-Decoder-B) Mean AP 27.7 #10 of 12 Archive leaderboard report
Zero Shot Segmentation Segmentation in the Wild SGinW_Team (X-Decoder-L-IN21K) Mean AP 26.6 #11 of 12 Archive leaderboard report
Zero Shot Segmentation Segmentation in the Wild SGinW_Team (X-Decoder-T) Mean AP 22.6 #12 of 12 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.

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