no code implementations • 2 Apr 2024 • Tahira Shehzadi, Khurram Azeem Hashmi, Didier Stricker, Muhammad Zeshan Afzal
In this paper, we address the limitations of the DETR-based semi-supervised object detection (SSOD) framework, particularly focusing on the challenges posed by the quality of object queries.
Ranked #1 on Semi-Supervised Object Detection on COCO
1 code implementation • ICCV 2023 • Khurram Azeem Hashmi, Goutham Kallempudi, Didier Stricker, Muhammamd Zeshan Afzal
Extracting useful visual cues for the downstream tasks is especially challenging under low-light vision.
no code implementations • 23 Jun 2023 • Tahira Shehzadi, Khurram Azeem Hashmi, Didier Stricker, Marcus Liwicki, Muhammad Zeshan Afzal
Upon integrating query modifications in the DETR, we outperform prior works and achieve new state-of-the-art results with the mAP of 96. 9\%, 95. 7\% and 99. 3\% on TableBank, PubLaynet, PubTables, respectively.
Ranked #3 on Document Layout Analysis on PubLayNet val
2 code implementations • 7 Jun 2023 • Tahira Shehzadi, Khurram Azeem Hashmi, Didier Stricker, Muhammad Zeshan Afzal
The astounding performance of transformers in natural language processing (NLP) has motivated researchers to explore their applications in computer vision tasks.
no code implementations • 4 May 2023 • Tahira Shehzadi, Khurram Azeem Hashmi, Didier Stricker, Marcus Liwicki, Muhammad Zeshan Afzal
Table detection is the task of classifying and localizing table objects within document images.
no code implementations • 12 Oct 2022 • Khurram Azeem Hashmi, Alain Pagani, Didier Stricker, Muhammamd Zeshan Afzal
We present a new, simple yet effective approach to uplift video object detection.
Ranked #14 on Video Object Detection on ImageNet VID
no code implementations • 5 Oct 2022 • Khurram Azeem Hashmi, Didier Stricker, Muhammamd Zeshan Afzal
Second, motivated by sequence-level semantic aggregation, we incorporate the attention-guided Semantic Proposal Feature Aggregation module to enhance object feature representation before detection.
Ranked #25 on Video Object Detection on ImageNet VID
no code implementations • 29 Apr 2021 • Khurram Azeem Hashmi, Marcus Liwicki, Didier Stricker, Muhammad Adnan Afzal, Muhammad Ahtsham Afzal, Muhammad Zeshan Afzal
Table understanding has substantially benefited from the recent breakthroughs in deep neural networks.
no code implementations • 21 Apr 2021 • Khurram Azeem Hashmi, Didier Stricker, Marcus Liwicki, Muhammad Noman Afzal, Muhammad Zeshan Afzal
Subsequently, these anchors are exploited to locate the rows and columns in tabular images.