15 citations · 67 across the 29 of their papers we have counts for
30 papers
DecoMoE: Decoupling Visual Propagation and Expert Computation for Efficient Multimodal MoE Inference
Xudong Tan, Peng Ye, Ming Xie +4
Multimodal mixture-of-experts (MoE) models combine sparse expert activation with visual-language capabilities, yet their inference remains costly because long visual-token sequence…
AeroGround: A Comprehensive Benchmark for Aerial-Ground Collaborative Reasoning
Shenghong Yi, Lin Zhang, Muzian Li +6
Vision-language models (VLMs) have been widely employed in understanding and reasoning tasks for unmanned aerial vehicles (UAVs). Existing UAV benchmarks primarily focus on aerial-…
ReMix: Towards a Unified View of Consistent Character Generation and Editing
Benjia Zhou, Bin Fu, Pei Cheng +3
Recent advances in large-scale text-to-image diffusion models (e.g., FLUX.1) have greatly improved visual fidelity in consistent character generation and editing. However, existing…
CTTS: Collective Test-Time Scaling
Zhende Song, Shengji Tang, Peng Ye +4
Test-time scaling (TTS) has emerged as a promising, training-free approach for enhancing large language model (LLM) performance. However, the efficacy of existing methods, such as…
Decouple and Orthogonalize: A Data-Free Framework for LoRA Merging
Shenghe Zheng, Hongzhi Wang, Chenyu Huang +5
With more open-source models available for diverse tasks, model merging has gained attention by combining models into one, reducing training, storage, and inference costs. Current…
Lightweight Model Pre-training via Language Guided Knowledge Distillation
Mingsheng Li, Lin Zhang, Mingzhen Zhu +4
This paper studies the problem of pre-training for small models, which is essential for many mobile devices. Current state-of-the-art methods on this problem transfer the represent…
DualMamba: A Lightweight Spectral-Spatial Mamba-Convolution Network for Hyperspectral Image Classification
Jiamu Sheng, Jingyi Zhou, Jiong Wang +2
The effectiveness and efficiency of modeling complex spectral-spatial relations are both crucial for Hyperspectral image (HSI) classification. Most existing methods based on CNNs a…
Adapter-X: A Novel General Parameter-Efficient Fine-Tuning Framework for Vision
Minglei Li, Peng Ye, Yongqi Huang +5
Parameter-efficient fine-tuning (PEFT) has become increasingly important as foundation models continue to grow in both popularity and size. Adapter has been particularly well-recei…
DreamFrame: Enhancing Video Understanding via Automatically Generated QA and Style-Consistent Keyframes
Zhende Song, Chenchen Wang, Jiamu Sheng +4
Recent large vision-language models (LVLMs) for video understanding are primarily fine-tuned with various videos scraped from online platforms. Existing datasets, such as ActivityN…
BridgeNet: Comprehensive and Effective Feature Interactions via Bridge Feature for Multi-task Dense Predictions
Jingdong Zhang, Jiayuan Fan, Peng Ye +5
Multi-task dense prediction aims at handling multiple pixel-wise prediction tasks within a unified network simultaneously for visual scene understanding. However, cross-task featur…
LL3DA: Visual Interactive Instruction Tuning for Omni-3D Understanding, Reasoning, and Planning
Sijin Chen, Xin Chen, Chi Zhang +6
Recent advances in Large Multimodal Models (LMM) have made it possible for various applications in human-machine interactions. However, developing LMMs that can comprehend, reason,…
PDF: Point Diffusion Implicit Function for Large-scale Scene Neural Representation
Yuhan Ding, Fukun Yin, Jiayuan Fan +6
Recent advances in implicit neural representations have achieved impressive results by sampling and fusing individual points along sampling rays in the sampling space. However, due…
VQ-NeRF: Vector Quantization Enhances Implicit Neural Representations
Yiying Yang, Wen Liu, Fukun Yin +4
Recent advancements in implicit neural representations have contributed to high-fidelity surface reconstruction and photorealistic novel view synthesis. However, the computational…
Exploring Multi-Timestep Multi-Stage Diffusion Features for Hyperspectral Image Classification
Jingyi Zhou, Jiamu Sheng, Jiayuan Fan +4
The effectiveness of spectral-spatial feature learning is crucial for the hyperspectral image (HSI) classification task. Diffusion models, as a new class of groundbreaking generati…
Boost Vision Transformer with GPU-Friendly Sparsity and Quantization
Chong Yu, Tao Chen, Zhongxue Gan +1
The transformer extends its success from the language to the vision domain. Because of the stacked self-attention and cross-attention blocks, the acceleration deployment of vision…
What Makes for Effective Few-shot Point Cloud Classification?
Chuangguan Ye, Hongyuan Zhu, Yongbin Liao +3
Due to the emergence of powerful computing resources and large-scale annotated datasets, deep learning has seen wide applications in our daily life. However, most current methods r…
Performance-aware Approximation of Global Channel Pruning for Multitask CNNs
Hancheng Ye, Bo Zhang, Tao Chen +2
Global channel pruning (GCP) aims to remove a subset of channels (filters) across different layers from a deep model without hurting the performance. Previous works focus on either…
A2S-NAS: Asymmetric Spectral-Spatial Neural Architecture Search For Hyperspectral Image Classification
Lin Zhan, Jiayuan Fan, Peng Ye +1
Existing deep learning-based hyperspectral image (HSI) classification works still suffer from the limitation of the fixed-sized receptive field, leading to difficulties in distinct…
JNDMix: JND-Based Data Augmentation for No-reference Image Quality Assessment
Jiamu Sheng, Jiayuan Fan, Peng Ye +1
Despite substantial progress in no-reference image quality assessment (NR-IQA), previous training models often suffer from over-fitting due to the limited scale of used datasets, r…
A Large-Scale Outdoor Multi-modal Dataset and Benchmark for Novel View Synthesis and Implicit Scene Reconstruction
Chongshan Lu, Fukun Yin, Xin Chen +3
Neural Radiance Fields (NeRF) has achieved impressive results in single object scene reconstruction and novel view synthesis, which have been demonstrated on many single modality a…
Instance-aware Model Ensemble With Distillation For Unsupervised Domain Adaptation
Weimin Wu, Jiayuan Fan, Tao Chen +3
The linear ensemble based strategy, i.e., averaging ensemble, has been proposed to improve the performance in unsupervised domain adaptation tasks. However, a typical UDA task is u…
Efficient Joint-Dimensional Search with Solution Space Regularization for Real-Time Semantic Segmentation
Peng Ye, Baopu Li, Tao Chen +6
Semantic segmentation is a popular research topic in computer vision, and many efforts have been made on it with impressive results. In this paper, we intend to search an optimal n…
Learning Cross-Image Object Semantic Relation in Transformer for Few-Shot Fine-Grained Image Classification
Bo Zhang, Jiakang Yuan, Baopu Li +3
Few-shot fine-grained learning aims to classify a query image into one of a set of support categories with fine-grained differences. Although learning different objects' local diff…
-DARTS: Beta-Decay Regularization for Differentiable Architecture Search
Peng Ye, Baopu Li, Yikang Li +3
Neural Architecture Search~(NAS) has attracted increasingly more attention in recent years because of its capability to design deep neural networks automatically. Among them, diffe…