Search Results for author: Sheng Zheng

Found 9 papers, 1 papers with code

Sora as an AGI World Model? A Complete Survey on Text-to-Video Generation

no code implementations8 Mar 2024 Joseph Cho, Fachrina Dewi Puspitasari, Sheng Zheng, Jingyao Zheng, Lik-Hang Lee, Tae-Ho Kim, Choong Seon Hong, Chaoning Zhang

The evolution of video generation from text, starting with animating MNIST numbers to simulating the physical world with Sora, has progressed at a breakneck speed over the past seven years.

Hallucination Text-to-Image Generation +3

MobileSAMv2: Faster Segment Anything to Everything

1 code implementation15 Dec 2023 Chaoning Zhang, Dongshen Han, Sheng Zheng, Jinwoo Choi, Tae-Ho Kim, Choong Seon Hong

The efficiency bottleneck of SegEvery with SAM, however, lies in its mask decoder because it needs to first generate numerous masks with redundant grid-search prompts and then perform filtering to obtain the final valid masks.

Decoder Knowledge Distillation +2

SAM Meets UAP: Attacking Segment Anything Model With Universal Adversarial Perturbation

no code implementations19 Oct 2023 Dongshen Han, Chaoning Zhang, Sheng Zheng, Chang Lu, Yang Yang, Heng Tao Shen

On top of the ablation study to understand various components in our proposed method, we shed light on the roles of positive and negative samples in making the generated UAP effective for attacking SAM.

Adversarial Attack Adversarial Robustness +1

Black-box Targeted Adversarial Attack on Segment Anything (SAM)

no code implementations16 Oct 2023 Sheng Zheng, Chaoning Zhang, Xinhong Hao

The task of TAA on SAM has been realized in a recent arXiv work in the white-box setup by assuming access to prompt and model, which is thus less practical.

Adversarial Attack

A Survey on Segment Anything Model (SAM): Vision Foundation Model Meets Prompt Engineering

no code implementations12 May 2023 Chaoning Zhang, Joseph Cho, Fachrina Dewi Puspitasari, Sheng Zheng, Chenghao Li, Yu Qiao, Taegoo Kang, Xinru Shan, Chenshuang Zhang, Caiyan Qin, Francois Rameau, Lik-Hang Lee, Sung-Ho Bae, Choong Seon Hong

The Segment Anything Model (SAM), developed by Meta AI Research, represents a significant breakthrough in computer vision, offering a robust framework for image and video segmentation.

Edge Detection model +4

A Survey on Audio Diffusion Models: Text To Speech Synthesis and Enhancement in Generative AI

no code implementations23 Mar 2023 Chenshuang Zhang, Chaoning Zhang, Sheng Zheng, Mengchun Zhang, Maryam Qamar, Sung-Ho Bae, In So Kweon

This work conducts a survey on audio diffusion model, which is complementary to existing surveys that either lack the recent progress of diffusion-based speech synthesis or highlight an overall picture of applying diffusion model in multiple fields.

Speech Enhancement Speech Synthesis +3

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