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20202024
most citedTransKD: Transformer Knowledge Distillation for Efficient Semantic Segmentation

27 citations · 127 across the 53 of their papers we have counts for

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Showing 2024 · cs.CVShow all

13 papers · 2 filters

cs.CV2024★ 1 cited

Deformable Mamba for Wide Field of View Segmentation

Jie Hu, Junwei Zheng, Jiale Wei +2

Recent advancements in the Mamba architecture, with its linear computational complexity, being a promising alternative to transformer architectures suffering from quadratic complex…

cs.CV2024

Solving Zero-Shot 3D Visual Grounding as Constraint Satisfaction Problems

Qihao Yuan, Kailai Li, Jiaming Zhang

3D visual grounding (3DVG) aims to locate objects in a 3D scene with natural language descriptions. Supervised methods have achieved decent accuracy, but have a closed vocabulary a…

cs.CV2024

OneBEV: Using One Panoramic Image for Bird's-Eye-View Semantic Mapping

Jiale Wei, Junwei Zheng, Ruiping Liu +3

In the field of autonomous driving, Bird's-Eye-View (BEV) perception has attracted increasing attention in the community since it provides more comprehensive information compared w…

cs.CV2024

@Bench: Benchmarking Vision-Language Models for Human-centered Assistive Technology

Xin Jiang, Junwei Zheng, Ruiping Liu +4

As Vision-Language Models (VLMs) advance, human-centered Assistive Technologies (ATs) for helping People with Visual Impairments (PVIs) are evolving into generalists, capable of pe…

cs.CV2024

Comb, Prune, Distill: Towards Unified Pruning for Vision Model Compression

Jonas Schmitt, Ruiping Liu, Junwei Zheng +2

Lightweight and effective models are essential for devices with limited resources, such as intelligent vehicles. Structured pruning offers a promising approach to model compression…

cs.CV2024

Open Panoramic Segmentation

Junwei Zheng, Ruiping Liu, Yufan Chen +5

Panoramic images, capturing a 360° field of view (FoV), encompass omnidirectional spatial information crucial for scene understanding. However, it is not only costly to obtain trai…

cs.CV2024

Referring Atomic Video Action Recognition

Kunyu Peng, Jia Fu, Kailun Yang +8

We introduce a new task called Referring Atomic Video Action Recognition (RAVAR), aimed at identifying atomic actions of a particular person based on a textual description and the…

cs.CV2024

Occlusion-Aware Seamless Segmentation

Yihong Cao, Jiaming Zhang, Hao Shi +5

Panoramic images can broaden the Field of View (FoV), occlusion-aware prediction can deepen the understanding of the scene, and domain adaptation can transfer across viewing domain…

cs.CV2024

AltChart: Enhancing VLM-based Chart Summarization Through Multi-Pretext Tasks

Omar Moured, Jiaming Zhang, M. Saquib Sarfraz +1

Chart summarization is a crucial task for blind and visually impaired individuals as it is their primary means of accessing and interpreting graphical data. Crafting high-quality d…

cs.CV2024★ 1 cited

RoDLA: Benchmarking the Robustness of Document Layout Analysis Models

Yufan Chen, Jiaming Zhang, Kunyu Peng +4

Before developing a Document Layout Analysis (DLA) model in real-world applications, conducting comprehensive robustness testing is essential. However, the robustness of DLA models…

cs.CV2024

Skeleton-Based Human Action Recognition with Noisy Labels

Yi Xu, Kunyu Peng, Di Wen +7

Understanding human actions from body poses is critical for assistive robots sharing space with humans in order to make informed and safe decisions about the next interaction. Howe…

cs.CV2024

Fourier Prompt Tuning for Modality-Incomplete Scene Segmentation

Ruiping Liu, Jiaming Zhang, Kunyu Peng +6

Integrating information from multiple modalities enhances the robustness of scene perception systems in autonomous vehicles, providing a more comprehensive and reliable sensory fra…

cs.CV2024★ 4 cited

LF Tracy: A Unified Single-Pipeline Approach for Salient Object Detection in Light Field Cameras

Fei Teng, Jiaming Zhang, Jiawei Liu +4

Leveraging rich information is crucial for dense prediction tasks. Light field (LF) cameras are instrumental in this regard, as they allow data to be sampled from various perspecti…