3 accepted papers
We present ReMatch, a framework that leverages the generative strength of MLLMs for multimodal retrieval. Previous approaches treated an MLLM as a simple encoder, ignoring its generative nature, and under-utilising its compositional reasoning and world knowledge. We train the embedding MLLM end-to-e
In this work we present Digital Life Project a framework utilizing language as the universal medium to build autonomous 3D characters who are capable of engaging in social interactions and expressing with articulated body motions thereby simulating life in a digital environment. Our framework compri…
Synthetic data has emerged as a promising source for 3D human research as it offers low-cost access to large-scale human datasets. To advance the diversity and annotation quality of human models, we introduce a new synthetic dataset, SynBody, with three appealing features: 1) a clothed parametric hu…