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20212023
most citedMulT: An End-to-End Multitask Learning Transformer

12 citations · 28 across the 10 of their papers we have counts for

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8 papers · 1 filter

cs.CV2023★ 4 cited

Customizing General-Purpose Foundation Models for Medical Report Generation

Bang Yang, Asif Raza, Yuexian Zou +1

Medical caption prediction which can be regarded as a task of medical report generation (MRG), requires the automatic generation of coherent and accurate captions for the given med…

cs.CV2023

De-coupling and De-positioning Dense Self-supervised Learning

Congpei Qiu, Tong Zhang, Wei Ke +2

Dense Self-Supervised Learning (SSL) methods address the limitations of using image-level feature representations when handling images with multiple objects. Although the dense fea…

cs.CV2023

TempSAL -- Uncovering Temporal Information for Deep Saliency Prediction

Bahar Aydemir, Ludo Hoffstetter, Tong Zhang +2

Deep saliency prediction algorithms complement the object recognition features, they typically rely on additional information, such as scene context, semantic relationships, gaze d…

cs.CV2022★ 2 cited

Increasing Visual Awareness in Multimodal Neural Machine Translation from an Information Theoretic Perspective

Baijun Ji, Tong Zhang, Yicheng Zou +2

Multimodal machine translation (MMT) aims to improve translation quality by equipping the source sentence with its corresponding image. Despite the promising performance, MMT model…

cs.CV2022★ 12 cited

MulT: An End-to-End Multitask Learning Transformer

Deblina Bhattacharjee, Tong Zhang, Sabine Süsstrunk +1

We propose an end-to-end Multitask Learning Transformer framework, named MulT, to simultaneously learn multiple high-level vision tasks, including depth estimation, semantic segmen…

cs.CV2022★ 1 cited

Leverage Your Local and Global Representations: A New Self-Supervised Learning Strategy

Tong Zhang, Congpei Qiu, Wei Ke +2

Self-supervised learning (SSL) methods aim to learn view-invariant representations by maximizing the similarity between the features extracted from different crops of the same imag…

cs.CV2021★ 1 cited

CLIP Meets Video Captioning: Concept-Aware Representation Learning Does Matter

Bang Yang, Tong Zhang, Yuexian Zou

For video captioning, "pre-training and fine-tuning" has become a de facto paradigm, where ImageNet Pre-training (INP) is usually used to encode the video content, then a task-orie…

cs.CV2021

Nondiscriminatory Treatment: a straightforward framework for multi-human parsing

Min Yan, Guoshan Zhang, Tong Zhang +1

Multi-human parsing aims to segment every body part of every human instance. Nearly all state-of-the-art methods follow the "detection first" or "segmentation first" pipelines. Dif…