4 citations · 12 across the 15 of their papers we have counts for
15 papers
When Vision Becomes Text: Visual Token Pruning via Cross-Modal Residual Guidance in VLMs
Congyang Ou, Ruike Song, Yang Zhou +3
Abundant visual information strengthens vision-language model (VLM) perception, yet massive visual tokens raise inference costs. Existing visual token pruning methods rely on simil…
Rethinking Practical and Efficient Quantization Calibration for Vision-Language Models
Zhenhao Shang, Haizhao Jing, Guoting Wei +4
Post-training quantization (PTQ) is a primary approach for deploying large language models without fine-tuning, and the quantized performance is often strongly affected by the cali…
Open-Text Aerial Detection: A Unified Framework For Aerial Visual Grounding And Detection
Guoting Wei, Xia Yuan, Yang Zhou +6
Open-Vocabulary Aerial Detection (OVAD) and Remote Sensing Visual Grounding (RSVG) have emerged as two key paradigms for aerial scene understanding. However, each paradigm suffers…
Unlocking Prototype Potential: An Efficient Tuning Framework for Few-Shot Class-Incremental Learning
Shengqin Jiang, Xiaoran Feng, Yuankai Qi +6
Few-shot class-incremental learning (FSCIL) seeks to continuously learn new classes from very limited samples while preserving previously acquired knowledge. Traditional methods of…
Open-Vocabulary Object Detection in UAV Imagery: A Review and Future Perspectives
Yang Zhou, Junjie Li, CongYang Ou +3
Due to its extensive applications, aerial image object detection has long been a hot topic in computer vision. In recent years, advancements in Unmanned Aerial Vehicles (UAV) techn…
UVLM: Benchmarking Video Language Model for Underwater World Understanding
Xizhe Xue, Yang Zhou, Dawei Yan +5
Recently, the remarkable success of large language models (LLMs) has achieved a profound impact on the field of artificial intelligence. Numerous advanced works based on LLMs have…
Not All Attention Heads Are What You Need: Refining CLIP's Image Representation with Attention Ablation
Feng Lin, Marco Chen, Haokui Zhang +3
This paper investigates the role of attention heads in CLIP's image encoder. Building on interpretability studies, we conduct an exhaustive analysis and find that certain heads, di…
Language Embedding Meets Dynamic Graph: A New Exploration for Neural Architecture Representation Learning
Haizhao Jing, Haokui Zhang, Zhenhao Shang +3
Neural Architecture Representation Learning aims to transform network models into feature representations for predicting network attributes, playing a crucial role in deploying and…
OS-W2S: An Automatic Labeling Engine for Language-Guided Open-Set Aerial Object Detection
Guoting Wei, Yu Liu, Xia Yuan +7
In recent years, language-guided open-set aerial object detection has gained significant attention due to its better alignment with real-world application needs. However, due to li…
REO-VLM: Transforming VLM to Meet Regression Challenges in Earth Observation
Xizhe Xue, Guoting Wei, Hao Chen +4
The rapid evolution of Vision Language Models (VLMs) has catalyzed significant advancements in artificial intelligence, expanding research across various disciplines, including Ear…
Efficient Adaptation of Pre-trained Vision Transformer via Householder Transformation
Wei Dong, Yuan Sun, Yiting Yang +7
A common strategy for Parameter-Efficient Fine-Tuning (PEFT) of pre-trained Vision Transformers (ViTs) involves adapting the model to downstream tasks by learning a low-rank adapta…
Advancements in Visual Language Models for Remote Sensing: Datasets, Capabilities, and Enhancement Techniques
Lijie Tao, Haokui Zhang, Haizhao Jing +4
Recently, the remarkable success of ChatGPT has sparked a renewed wave of interest in artificial intelligence (AI), and the advancements in visual language models (VLMs) have pushe…
RT-OVAD: Real-Time Open-Vocabulary Aerial Object Detection via Image-Text Collaboration
Guoting Wei, Xia Yuan, Yu Liu +7
Aerial object detection plays a crucial role in numerous applications. However, most existing methods focus on detecting predefined object categories, limiting their applicability…
Gradient Information Guided Deraining with A Novel Network and Adversarial Training
Yinglong Wang, Haokui Zhang, Yu Liu +2
In recent years, deep learning based methods have made significant progress in rain-removing. However, the existing methods usually do not have good generalization ability, which l…
Meta Learning with Differentiable Closed-form Solver for Fast Video Object Segmentation
Yu Liu, Lingqiao Liu, Haokui Zhang +2
This paper tackles the problem of video object segmentation. We are specifically concerned with the task of segmenting all pixels of a target object in all frames, given the annota…