21 citations · 34 across the 10 of their papers we have counts for
5 papers · 1 filter
Lean-SAM2: Target-Anchored Memory and Encoder Acceleration for SAM2
Xudong Ouyang, Wenlun Zhang, Yimin Xu +2
The Segment Anything Model 2 (SAM2) has advanced temporal promptable segmentation, yet its deployment remains hindered by heavy memory cross-attention overhead and redundant full-f…
Detect in Any Scene: An Agentic Framework for Object Detection with Experience-Aware Reasoning
Wenlun Zhang, Jun Yin, Kentaro Yoshioka
Object detection in real-world scenarios remains challenging due to diverse image degradations and heterogeneous object distributions, which significantly hinder the generalization…
Neural Reconstruction of LiDAR Point Clouds under Jamming Attacks via Full-Waveform Representation and Simultaneous Laser Sensing
Ryo Yoshida, Takami Sato, Wenlun Zhang +7
LiDAR sensors are critical for autonomous driving perception, yet remain vulnerable to spoofing attacks. Jamming attacks inject high-frequency laser pulses that completely blind Li…
D4C: Data-Free Quantization for Contrastive Language-Image Pre-training Models
Wenlun Zhang, Yunshan Zhong, Zihao Ding +2
Data-Free Quantization (DFQ) offers a practical solution for model compression without requiring access to real data, making it particularly attractive in privacy-sensitive scenari…
AHCQ-SAM: Toward Accurate and Hardware-Compatible Post-Training Segment Anything Model Quantization
Wenlun Zhang, Yunshan Zhong, Weiqi Yan +3
The Segment Anything Model (SAM) has revolutionized image and video segmentation with its powerful zero-shot capabilities. However, its massive parameter scale and high computation…