230 citations · 331 across the 19 of their papers we have counts for
12 papers · 1 filter
SJD-PAC: Accelerating Speculative Jacobi Decoding via Proactive Drafting and Adaptive Continuation
Jialiang Kang, Han Shu, Wenshuo Li +2
Speculative Jacobi Decoding (SJD) offers a draft-model-free approach to accelerate autoregressive text-to-image synthesis. However, the high-entropy nature of visual generation yie…
Visual-textual Dermatoglyphic Animal Biometrics: A First Case Study on Panthera tigris
Wenshuo Li, Majid Mirmehdi, Tilo Burghardt
Biologists have long combined visuals with textual field notes to re-identify (Re-ID) animals. Contemporary AI tools automate this for species with distinctive morphological featur…
ViSpec: Accelerating Vision-Language Models with Vision-Aware Speculative Decoding
Jialiang Kang, Han Shu, Wenshuo Li +2
Speculative decoding is a widely adopted technique for accelerating inference in large language models (LLMs), yet its application to vision-language models (VLMs) remains underexp…
Align-KD: Distilling Cross-Modal Alignment Knowledge for Mobile Vision-Language Model Enhancement
Qianhan Feng, Wenshuo Li, Tong Lin +1
Vision-Language Models (VLMs) bring powerful understanding and reasoning capabilities to multimodal tasks. Meanwhile, the great need for capable aritificial intelligence on mobile…
Full-Stage Pseudo Label Quality Enhancement for Weakly-supervised Temporal Action Localization
Qianhan Feng, Wenshuo Li, Tong Lin +1
Weakly-supervised Temporal Action Localization (WSTAL) aims to localize actions in untrimmed videos using only video-level supervision. Latest WSTAL methods introduce pseudo label…
No Time to Waste: Squeeze Time into Channel for Mobile Video Understanding
Yingjie Zhai, Wenshuo Li, Yehui Tang +2
Current architectures for video understanding mainly build upon 3D convolutional blocks or 2D convolutions with additional operations for temporal modeling. However, these methods…
TinySAM: Pushing the Envelope for Efficient Segment Anything Model
Han Shu, Wenshuo Li, Yehui Tang +5
Recently segment anything model (SAM) has shown powerful segmentation capability and has drawn great attention in computer vision fields. Massive following works have developed var…
CNN-transformer mixed model for object detection
Wenshuo Li
Object detection, one of the three main tasks of computer vision, has been used in various applications. The main process is to use deep neural networks to extract the features of…
Brain-inspired Multilayer Perceptron with Spiking Neurons
Wenshuo Li, Hanting Chen, Jianyuan Guo +2
Recently, Multilayer Perceptron (MLP) becomes the hotspot in the field of computer vision tasks. Without inductive bias, MLPs perform well on feature extraction and achieve amazing…
Physical Adversarial Attack on Vehicle Detector in the Carla Simulator
Tong Wu, Xuefei Ning, Wenshuo Li +3
In this paper, we tackle the issue of physical adversarial examples for object detectors in the wild. Specifically, we proposed to generate adversarial patterns to be applied on ve…
Evaluating Efficient Performance Estimators of Neural Architectures
Xuefei Ning, Changcheng Tang, Wenshuo Li +4
Conducting efficient performance estimations of neural architectures is a major challenge in neural architecture search (NAS). To reduce the architecture training costs in NAS, one…
DSA: More Efficient Budgeted Pruning via Differentiable Sparsity Allocation
Xuefei Ning, Tianchen Zhao, Wenshuo Li +3
Budgeted pruning is the problem of pruning under resource constraints. In budgeted pruning, how to distribute the resources across layers (i.e., sparsity allocation) is the key pro…