11 papers
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…
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…
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…
KVSlimmer: Theoretical Insights and Practical Optimizations for Asymmetric KV Merging
Lianjun Liu, Hongli An, Weiqi Yan +4
The growing computational and memory demands of the Key-Value (KV) cache significantly limit the ability of Large Language Models (LLMs). While KV merging has emerged as a promisin…
Test-Time Iterative Error Correction for Efficient Diffusion Models
Yunshan Zhong, Weiqi Yan, Yuxin Zhang
With the growing demand for high-quality image generation on resource-constrained devices, efficient diffusion models have received increasing attention. However, such models suffe…