activity
20232026
most citedAn Open and Comprehensive Pipeline for Unified Object Grounding and Detection

7 citations · 15 across the 9 of their papers we have counts for

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Showing 2024Show all

6 papers · 1 filter

cs.CV2024

Revisiting the Integration of Convolution and Attention for Vision Backbone

Lei Zhu, Xinjiang Wang, Wayne Zhang +1

Convolutions (Convs) and multi-head self-attentions (MHSAs) are typically considered alternatives to each other for building vision backbones. Although some works try to integrate…

cs.CV2024

Text4Seg: Reimagining Image Segmentation as Text Generation

Mengcheng Lan, Chaofeng Chen, Yue Zhou +5

Multimodal Large Language Models (MLLMs) have shown exceptional capabilities in vision-language tasks; however, effectively integrating image segmentation into these models remains…

cs.CV2024

ProxyCLIP: Proxy Attention Improves CLIP for Open-Vocabulary Segmentation

Mengcheng Lan, Chaofeng Chen, Yiping Ke +3

Open-vocabulary semantic segmentation requires models to effectively integrate visual representations with open-vocabulary semantic labels. While Contrastive Language-Image Pre-tra…

cs.CV2024

ClearCLIP: Decomposing CLIP Representations for Dense Vision-Language Inference

Mengcheng Lan, Chaofeng Chen, Yiping Ke +3

Despite the success of large-scale pretrained Vision-Language Models (VLMs) especially CLIP in various open-vocabulary tasks, their application to semantic segmentation remains cha…

cs.CL2024★ 1 cited

RelayAttention for Efficient Large Language Model Serving with Long System Prompts

Lei Zhu, Xinjiang Wang, Wayne Zhang +1

A practical large language model (LLM) service may involve a long system prompt, which specifies the instructions, examples, and knowledge documents of the task and is reused acros…

cs.CV2024★ 7 cited

An Open and Comprehensive Pipeline for Unified Object Grounding and Detection

Xiangyu Zhao, Yicheng Chen, Shilin Xu +4

Grounding-DINO is a state-of-the-art open-set detection model that tackles multiple vision tasks including Open-Vocabulary Detection (OVD), Phrase Grounding (PG), and Referring Exp…