2 citations · 2 across the 7 of their papers we have counts for
9 papers
StreamVibe: Proactive Video Agents for Evolving User Intent
Chengzhi Liu, Yuxiang Lai, Yuzhe Yang +13
Vision-language models are shifting from offline passive understanding toward online proactive interaction. However, prevailing methods largely rely on explicit requests while miss…
WorldMemArena: Evaluating Multimodal Agent Memory Through Action-World Interaction
Chengzhi Liu, Yuzhe Yang, Sophia Xiao Pu +14
Multimodal large language models are increasingly deployed as long-horizon agents, where memory must do more than recall: it must track an evolving world, revise what has gone stal…
Do 3D Large Language Models Really Understand 3D Spatial Relationships?
Xianzheng Ma, Tao Sun, Shuai Chen +7
Recent 3D Large-Language Models (3D-LLMs) claim to understand 3D worlds, especially spatial relationships among objects. Yet, we find that simply fine-tuning a language model on te…
Selfi: Self Improving Reconstruction Engine via 3D Geometric Feature Alignment
Youming Deng, Songyou Peng, Junyi Zhang +5
Novel View Synthesis (NVS) has traditionally relied on models with explicit 3D inductive biases combined with known camera parameters from Structure-from-Motion (SfM) beforehand. R…
Splat4D: Diffusion-Enhanced 4D Gaussian Splatting for Temporally and Spatially Consistent Content Creation
Minghao Yin, Yukang Cao, Songyou Peng +1
Generating high-quality 4D content from monocular videos for applications such as digital humans and AR/VR poses challenges in ensuring temporal and spatial consistency, preserving…
Visual Chronicles: Using Multimodal LLMs to Analyze Massive Collections of Images
Boyang Deng, Songyou Peng, Kyle Genova +4
We present a system using Multimodal LLMs (MLLMs) to analyze a large database with tens of millions of images captured at different times, with the aim of discovering patterns in t…
SplatTalk: 3D VQA with Gaussian Splatting
Anh Thai, Songyou Peng, Kyle Genova +2
Language-guided 3D scene understanding is important for advancing applications in robotics, AR/VR, and human-computer interaction, enabling models to comprehend and interact with 3…
Prompting Depth Anything for 4K Resolution Accurate Metric Depth Estimation
Haotong Lin, Sida Peng, Jingxiao Chen +7
Prompts play a critical role in unleashing the power of language and vision foundation models for specific tasks. For the first time, we introduce prompting into depth foundation m…
Parameter-Efficient Orthogonal Finetuning via Butterfly Factorization
Weiyang Liu, Zeju Qiu, Yao Feng +11
Large foundation models are becoming ubiquitous, but training them from scratch is prohibitively expensive. Thus, efficiently adapting these powerful models to downstream tasks is…