1.1k citations · 1.1k across the 11 of their papers we have counts for
13 papers
RA-CFGCache: From Branch-Level Criteria to Guided-Risk Control under Classifier-Free Guidance
Yiming Liu, Ben Wan, Tongxuan Liu +5
Diffusion models enable high-quality visual generation, but iterative denoising remains computationally expensive, especially under classifier-free guidance (CFG), which requires b…
FastOCR: Dynamic Visual Fixation via KV Cache Pruning for Efficient Document Parsing
Zihan Tang, Leqi Shen, Hui Chen +7
Vision-Language Models (VLMs) have shown strong promise on Optical Character Recognition (OCR), yet the sheer number of visual tokens required to encode dense documents incurs proh…
LSNet: See Large, Focus Small
Ao Wang, Hui Chen, Zijia Lin +2
Vision network designs, including Convolutional Neural Networks and Vision Transformers, have significantly advanced the field of computer vision. Yet, their complex computations p…
YOLOE: Real-Time Seeing Anything
Ao Wang, Lihao Liu, Hui Chen +3
Object detection and segmentation are widely employed in computer vision applications, yet conventional models like YOLO series, while efficient and accurate, are limited by predef…
YOLO-UniOW: Efficient Universal Open-World Object Detection
Lihao Liu, Juexiao Feng, Hui Chen +4
Traditional object detection models are constrained by the limitations of closed-set datasets, detecting only categories encountered during training. While multimodal models have e…
Promptable Anomaly Segmentation with SAM Through Self-Perception Tuning
Hui-Yue Yang, Hui Chen, Ao Wang +7
Segment Anything Model (SAM) has made great progress in anomaly segmentation tasks due to its impressive generalization ability. However, existing methods that directly apply SAM t…
[CLS] Token Tells Everything Needed for Training-free Efficient MLLMs
Ao Wang, Fengyuan Sun, Hui Chen +3
Multimodal Large Language Models (MLLMs) have recently demonstrated strong performance across a wide range of vision-language tasks, garnering significant attention in the computer…
PrefixKV: Adaptive Prefix KV Cache is What Vision Instruction-Following Models Need for Efficient Generation
Ao Wang, Hui Chen, Jiaxin Li +6
Recently, large vision-language models (LVLMs) have rapidly gained popularity for their strong generation and reasoning capabilities given diverse multimodal inputs. However, these…
YOLOv10: Real-Time End-to-End Object Detection
Ao Wang, Hui Chen, Lihao Liu +4
Over the past years, YOLOs have emerged as the predominant paradigm in the field of real-time object detection owing to their effective balance between computational cost and detec…
RepViT-SAM: Towards Real-Time Segmenting Anything
Ao Wang, Hui Chen, Zijia Lin +2
Segment Anything Model (SAM) has shown impressive zero-shot transfer performance for various computer vision tasks recently. However, its heavy computation costs remain daunting fo…
CAIT: Triple-Win Compression towards High Accuracy, Fast Inference, and Favorable Transferability For ViTs
Ao Wang, Hui Chen, Zijia Lin +3
Vision Transformers (ViTs) have emerged as state-of-the-art models for various vision tasks recently. However, their heavy computation costs remain daunting for resource-limited de…
RepViT: Revisiting Mobile CNN From ViT Perspective
Ao Wang, Hui Chen, Zijia Lin +2
Recently, lightweight Vision Transformers (ViTs) demonstrate superior performance and lower latency, compared with lightweight Convolutional Neural Networks (CNNs), on resource-con…
Exploring Structured Semantic Prior for Multi Label Recognition with Incomplete Labels
Zixuan Ding, Ao Wang, Hui Chen +5
Multi-label recognition (MLR) with incomplete labels is very challenging. Recent works strive to explore the image-to-label correspondence in the vision-language model, \ie, CLIP,…