3 citations · 4 across the 6 of their papers we have counts for
6 papers
Multimodal Unlearning Across Vision, Language, Video, and Audio: Survey of Methods, Datasets, and Benchmarks
Nobin Sarwar, Shubhashis Roy Dipta, Zheyuan Liu +1
With the growing adoption of VLMs, DMs, LLMs, and AFMs, these multimodal foundation models can inadvertently encode sensitive, copyrighted, biased, or unsafe cross-modal associatio…
Two-Stream Interactive Joint Learning of Scene Parsing and Geometric Vision Tasks
Guanfeng Tang, Hongbo Zhao, Ziwei Long +5
Inspired by the human visual system, which operates on two parallel yet interactive streams for contextual and spatial understanding, this article presents Two Interactive Streams…
Can video generation replace cinematographers? Research on the cinematic language of generated video
Xiaozhe Li, Kai WU, Siyi Yang +12
Recent advancements in text-to-video (T2V) generation have leveraged diffusion models to enhance visual coherence in videos synthesized from textual descriptions. However, existing…
GenAI-Bench: Evaluating and Improving Compositional Text-to-Visual Generation
Baiqi Li, Zhiqiu Lin, Deepak Pathak +8
While text-to-visual models now produce photo-realistic images and videos, they struggle with compositional text prompts involving attributes, relationships, and higher-order reaso…
Evaluating Text-to-Visual Generation with Image-to-Text Generation
Zhiqiu Lin, Deepak Pathak, Baiqi Li +5
Despite significant progress in generative AI, comprehensive evaluation remains challenging because of the lack of effective metrics and standardized benchmarks. For instance, the…
GraFT: Gradual Fusion Transformer for Multimodal Re-Identification
Haoli Yin, Jiayao Li, Eva Schiller +2
Object Re-Identification (ReID) is pivotal in computer vision, witnessing an escalating demand for adept multimodal representation learning. Current models, although promising, rev…