most citedHardware Accelerator for Adversarial Attacks on Deep Learning Neural Networks

4 citations · 9 across the 3 of their papers we have counts for

collaborators

8 papers

cs.CV2025

MIND-Edit: MLLM Insight-Driven Editing via Language-Vision Projection

Shuyu Wang, Weiqi Li, Qian Wang +2

Recent advances in AI-generated content (AIGC) have significantly accelerated image editing techniques, driving increasing demand for diverse and fine-grained edits. Despite these…

cs.CV20241 cited

HiCoM: Hierarchical Coherent Motion for Streamable Dynamic Scene with 3D Gaussian Splatting

Qiankun Gao, Jiarui Meng, Chengxiang Wen +2

The online reconstruction of dynamic scenes from multi-view streaming videos faces significant challenges in training, rendering and storage efficiency. Harnessing superior learnin…

cs.CV2024

CPA: Camera-pose-awareness Diffusion Transformer for Video Generation

Yuelei Wang, Jian Zhang, Pengtao Jiang +3

Despite the significant advancements made by Diffusion Transformer (DiT)-based methods in video generation, there remains a notable gap with controllable camera pose perspectives.…

cs.CV2024

Large Spatial Model: End-to-end Unposed Images to Semantic 3D

Zhiwen Fan, Jian Zhang, Wenyan Cong +10

Reconstructing and understanding 3D structures from a limited number of images is a well-established problem in computer vision. Traditional methods usually break this task into mu…

cs.CV202330 cited

CRoSS: Diffusion Model Makes Controllable, Robust and Secure Image Steganography

Jiwen Yu, Xuanyu Zhang, Youmin Xu +1

Current image steganography techniques are mainly focused on cover-based methods, which commonly have the risk of leaking secret images and poor robustness against degraded contain…

cs.RO2022

The Foreseeable Future: Self-Supervised Learning to Predict Dynamic Scenes for Indoor Navigation

Hugues Thomas, Jian Zhang, Timothy D. Barfoot

We present a method for generating, predicting, and using Spatiotemporal Occupancy Grid Maps (SOGM), which embed future semantic information of real dynamic scenes. We present an a…