14 citations · 14 across the 18 of their papers we have counts for
10 papers · 1 filter
LoSA: Near-Lossless Sparse Attention for Training-Free Video Diffusion Acceleration
Enhuai Liu, Yunke Wang, Yutong Wang +2
Video diffusion transformers are costly to sample: every denoising step applies self-attention over a long 3D token sequence, a quadratic cost that dominates as resolution and dura…
Early Semantic Grounding in Image Editing Models for Zero-Shot Referring Image Segmentation
Jingxuan He, Xiyu Wang, Yunke Wang +2
Instruction-based image editing (IIE) models have recently demonstrated strong capability in modifying specific image regions according to natural language instructions, which impl…
UniV2D: Bridging Visual Restoration and Semantic Perception for Underwater Salient Object Detection
Laibin Chang, Shaodong Wang, Yunke Wang +4
Underwater salient object detection (USOD) plays a vital role in marine vision tasks but remains fundamentally challenging due to severe visual degradation, such as selective absor…
Seeing Realism from Simulation: Efficient Video Transfer for Vision-Language-Action Data Augmentation
Chenyu Hui, Xiaodi Huang, Siyu Xu +5
Vision-language-action (VLA) models typically rely on large-scale real-world videos, whereas simulated data, despite being inexpensive and highly parallelizable to collect, often s…
Efficient Conditional Generation on Scale-based Visual Autoregressive Models
Jiaqi Liu, Tao Huang, Chang Xu
Recent advances in autoregressive (AR) models have demonstrated their potential to rival diffusion models in image synthesis. However, for complex spatially-conditioned generation,…
Rethinking Causal Mask Attention for Vision-Language Inference
Xiaohuan Pei, Tao Huang, YanXiang Ma +1
Causal attention has become a foundational mechanism in autoregressive vision-language models (VLMs), unifying textual and visual inputs under a single generative framework. Howeve…
Learning Mask Invariant Mutual Information for Masked Image Modeling
Tao Huang, Yanxiang Ma, Shan You +1
Masked autoencoders (MAEs) represent a prominent self-supervised learning paradigm in computer vision. Despite their empirical success, the underlying mechanisms of MAEs remain ins…
Cross-Self KV Cache Pruning for Efficient Vision-Language Inference
Xiaohuan Pei, Tao Huang, Chang Xu
KV cache pruning has emerged as a promising technique for reducing memory and computation costs in long-context auto-regressive generation. Existing methods for vision-language mod…
Training-free Composite Scene Generation for Layout-to-Image Synthesis
Jiaqi Liu, Tao Huang, Chang Xu
Recent breakthroughs in text-to-image diffusion models have significantly advanced the generation of high-fidelity, photo-realistic images from textual descriptions. Yet, these mod…
EfficientVMamba: Atrous Selective Scan for Light Weight Visual Mamba
Xiaohuan Pei, Tao Huang, Chang Xu
Prior efforts in light-weight model development mainly centered on CNN and Transformer-based designs yet faced persistent challenges. CNNs adept at local feature extraction comprom…