4 citations · 12 across the 15 of their papers we have counts for
13 papers · 1 filter
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…
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…
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…