228 citations · 381 across the 27 of their papers we have counts for
27 papers
M: Dual-Memory Augmentation for Long-Horizon Web Agents via Trajectory Summarization and Insight Retrieval
Dawei Yan, Haokui Zhang, Guangda Huzhang +8
Multimodal Large Language Models (MLLMs) based agents have demonstrated remarkable potential in autonomous web navigation. However, handling long-horizon tasks remains a critical b…
TRIO: Token Reduction via Inference-Objective Guidance for Efficient Vision-Language Models
Haokui Zhang, Congyang Ou, Dawei Yan +5
Recently, reducing redundant visual tokens in vision-language models (VLMs) to accelerate VLM inference has emerged as a hot topic. However, most existing methods rely on heuristic…
CC-Pan: Channel-wise Compression based Diffusion for Efficient Pan-Sharpening
Junjie Li, Congyang Ou, Haokui Zhang +3
Recently, diffusion models have brought novel insights to pan-sharpening and notably boosted fusion precision. However, most existing models perform diffusion in the pixel space an…
Teaching Prompts to Coordinate: Hierarchical Layer-Grouped Prompt Tuning for Continual Learning
Shengqin Jiang, Tianqi Kong, Yuankai Qi +5
Prompt-based continual learning methods fine-tune only a small set of additional learnable parameters while keeping the pre-trained model's parameters frozen. It enables efficient…
ProgRoCC: A Progressive Approach to Rough Crowd Counting
Shengqin Jiang, Linfei Li, Haokui Zhang +6
As the number of individuals in a crowd grows, enumeration-based techniques become increasingly infeasible and their estimates increasingly unreliable. We propose instead an estima…
MMCR: Advancing Visual Language Model in Multimodal Multi-Turn Contextual Reasoning
Dawei Yan, Yang Li, Qing-Guo Chen +4
Compared to single-turn dialogue, multi-turn dialogue involving multiple images better aligns with the needs of real-world human-AI interactions. Additionally, as training data, it…
TG-LLaVA: Text Guided LLaVA via Learnable Latent Embeddings
Dawei Yan, Pengcheng Li, Yang Li +7
Currently, inspired by the success of vision-language models (VLMs), an increasing number of researchers are focusing on improving VLMs and have achieved promising results. However…
3D-RCNet: Learning from Transformer to Build a 3D Relational ConvNet for Hyperspectral Image Classification
Haizhao Jing, Liuwei Wan, Xizhe Xue +2
Recently, the Vision Transformer (ViT) model has replaced the classical Convolutional Neural Network (ConvNet) in various computer vision tasks due to its superior performance. Eve…
Bridging Sensor Gaps via Attention Gated Tuning for Hyperspectral Image Classification
Xizhe Xue, Haokui Zhang, Haizhao Jing +3
Data-hungry HSI classification methods require high-quality labeled HSIs, which are often costly to obtain. This characteristic limits the performance potential of data-driven meth…
NAR-Former V2: Rethinking Transformer for Universal Neural Network Representation Learning
Yun Yi, Haokui Zhang, Rong Xiao +2
As more deep learning models are being applied in real-world applications, there is a growing need for modeling and learning the representations of neural networks themselves. An e…
Teacher Agent: A Knowledge Distillation-Free Framework for Rehearsal-based Video Incremental Learning
Shengqin Jiang, Yaoyu Fang, Haokui Zhang +4
Rehearsal-based video incremental learning often employs knowledge distillation to mitigate catastrophic forgetting of previously learned data. However, this method faces two major…
NAR-Former: Neural Architecture Representation Learning towards Holistic Attributes Prediction
Yun Yi, Haokui Zhang, Wenze Hu +2
With the wide and deep adoption of deep learning models in real applications, there is an increasing need to model and learn the representations of the neural networks themselves.…
Fcaformer: Forward Cross Attention in Hybrid Vision Transformer
Haokui Zhang, Wenze Hu, Xiaoyu Wang
Currently, one main research line in designing a more efficient vision transformer is reducing the computational cost of self attention modules by adopting sparse attention or usin…
ParCNetV2: Oversized Kernel with Enhanced Attention
Ruihan Xu, Haokui Zhang, Wenze Hu +2
Transformers have shown great potential in various computer vision tasks. By borrowing design concepts from transformers, many studies revolutionized CNNs and showed remarkable res…
Fast-ParC: Capturing Position Aware Global Feature for ConvNets and ViTs
Tao Yang, Haokui Zhang, Wenze Hu +2
Transformer models have made tremendous progress in various fields in recent years. In the field of computer vision, vision transformers (ViTs) also become strong alternatives to c…
ParC-Net: Position Aware Circular Convolution with Merits from ConvNets and Transformer
Haokui Zhang, Wenze Hu, Xiaoyu Wang
Recently, vision transformers started to show impressive results which outperform large convolution based models significantly. However, in the area of small models for mobile or r…
Grafting Transformer on Automatically Designed Convolutional Neural Network for Hyperspectral Image Classification
Xizhe Xue, Haokui Zhang, Bei Fang +2
Hyperspectral image (HSI) classification has been a hot topic for decides, as hyperspectral images have rich spatial and spectral information and provide strong basis for distingui…
Connecting Compression Spaces with Transformer for Approximate Nearest Neighbor Search
Haokui Zhang, Buzhou Tang, Wenze Hu +1
We propose a generic feature compression method for Approximate Nearest Neighbor Search (ANNS) problems, which speeds up existing ANNS methods in a plug-and-play manner. Specifical…
Pseudo-LiDAR Based Road Detection
Libo Sun, Haokui Zhang, Wei Yin
Road detection is a critically important task for self-driving cars. By employing LiDAR data, recent works have significantly improved the accuracy of road detection. Relying on Li…
3D-ANAS: 3D Asymmetric Neural Architecture Search for Fast Hyperspectral Image Classification
Haokui Zhang, Chengrong Gong, Yunpeng Bai +2
Hyperspectral images involve abundant spectral and spatial information, playing an irreplaceable role in land-cover classification. Recently, based on deep learning technologies, a…
Hyperspectral Classification Based on Lightweight 3-D-CNN With Transfer Learning
Haokui Zhang, Ying Li, Yenan Jiang +3
Recently, hyperspectral image (HSI) classification approaches based on deep learning (DL) models have been proposed and shown promising performance. However, because of very limite…
Memory-Efficient Hierarchical Neural Architecture Search for Image Restoration
Haokui Zhang, Ying Li, Hao Chen +3
Recently, much attention has been spent on neural architecture search (NAS), aiming to outperform those manually-designed neural architectures on high-level vision recognition task…
Hyperspectral Image Classification with Spatial Consistence Using Fully Convolutional Spatial Propagation Network
Yenan Jiang, Ying Li, Shanrong Zou +2
In recent years, deep convolutional neural networks (CNNs) have shown impressive ability to represent hyperspectral images (HSIs) and achieved encouraging results in HSI classifica…
Hyperspectral Classification Based on 3D Asymmetric Inception Network with Data Fusion Transfer Learning
Haokui Zhang, Yu Liu, Bei Fang +3
Hyperspectral image(HSI) classification has been improved with convolutional neural network(CNN) in very recent years. Being different from the RGB datasets, different HSI datasets…