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20232026
most citedParameter-Efficient Orthogonal Finetuning via Butterfly Factorization

2 citations · 2 across the 7 of their papers we have counts for

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7 papers · 1 filter

cs.CV2026

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…

cs.CV2026

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…

cs.CV2025

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…

cs.CV2025

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…

cs.CV2025

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…

cs.CV2025

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…

cs.CV2024

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…