3 citations · 8 across the 20 of their papers we have counts for
24 papers
Caption-once, Frames-on-Demand: Visual-Need Routing for Budget-Aware Agentic Long Video Understanding
Weitong Cai, Hang Zhang, Yukai Huang +6
Long-video understanding on edge devices must reason over hours of content under tight compute and bandwidth budgets. Subsampling visual tokens loses temporal structure, while text…
Video Generative Models as Geometry Learner
Haosen Yang, Jifei Song, Zhensong Zhang +2
Recent generative approaches to geometry estimation adapt pretrained image diffusion models and treat the task as image-conditioned generation. Leveraging off-the-shelf image diffu…
Each Judge Its Own Yardstick: Discovering Per-VLM Taxonomies for Physical Video Evaluation
Yu Cao, Ziquan Liu, Zhensong Zhang +3
Maintaining physical consistency in video generators and world models increasingly relies on vision-language models (VLMs) as automated judges that provide reward signals, ranking…
TriMotion: Modality-Agnostic Camera Control for Video Generation
Seunghyun Shin, Jifei Song, Wooseok Jeon +2
Camera motion control is essential for directing viewpoint changes in generative systems. However, existing methods typically condition the generation process on a single specific…
LiteVSR: Lightweight Adaptation of Frozen Diffusion Transformers for Video Super-Resolution
Yu Cao, Ziquan Liu, Zhensong Zhang +3
Adapting large-scale pre-trained video generators for Video Super-Resolution (VSR) in novel domains remains computationally prohibitive. Methods that reformulate generation as dire…
Diffusion-Based Makeup Transfer with Facial Region-Aware Makeup Features
Zheng Gao, Debin Meng, Yunqi Miao +4
Current diffusion-based makeup transfer methods commonly use the makeup information encoded by off-the-shelf foundation models (e.g., CLIP) as condition to preserve the makeup styl…
FG-Portrait: 3D Flow Guided Editable Portrait Animation
Yating Xu, Yunqi Miao, Evangelos Ververas +2
Motion transfer from the driving to the source portrait remains a key challenge in the portrait animation. Current diffusion-based approaches condition only on the driving motion,…
Color When It Counts: Grayscale-Guided Online Triggering for Always-On Streaming Video Sensing
Weitong Cai, Hang Zhang, Yukai Huang +5
Always-on sensing is essential for next-generation edge/wearable AI systems, yet continuous high-fidelity RGB video capture remains prohibitively expensive for resource-constrained…
Relax Forcing: Relaxed KV-Memory for Consistent Long Video Generation
Zengqun Zhao, Yanzuo Lu, Ziquan Liu +3
Autoregressive video diffusion has recently emerged as a promising paradigm for long-video generation, enabling causal synthesis beyond the temporal limits of bidirectional models.…
LatSearch: Latent Reward-Guided Search for Faster Inference-Time Scaling in Video Diffusion
Zengqun Zhao, Ziquan Liu, Yu Cao +5
The recent success of inference-time scaling in large language models has inspired similar explorations in video diffusion. In particular, motivated by the existence of "golden noi…
Optimizing Multimodal LLMs for Egocentric Video Understanding: A Solution for the HD-EPIC VQA Challenge
Sicheng Yang, Yukai Huang, Shitong Sun +4
Multimodal Large Language Models (MLLMs) struggle with complex video QA benchmarks like HD-EPIC VQA due to ambiguous queries/options, poor long-range temporal reasoning, and non-st…
Plug-and-Play Clarifier: A Zero-Shot Multimodal Framework for Egocentric Intent Disambiguation
Sicheng Yang, Yukai Huang, Weitong Cai +6
The performance of egocentric AI agents is fundamentally limited by multimodal intent ambiguity. This challenge arises from a combination of underspecified language, imperfect visu…
Unlocking the Potential of Diffusion Priors in Blind Face Restoration
Yunqi Miao, Zhiyu Qu, Mingqi Gao +4
Although diffusion prior is rising as a powerful solution for blind face restoration (BFR), the inherent gap between the vanilla diffusion model and BFR settings hinders its seamle…
UniGS: Unified Language-Image-3D Pretraining with Gaussian Splatting
Haoyuan Li, Yanpeng Zhou, Tao Tang +5
Recent advancements in multi-modal 3D pre-training methods have shown promising efficacy in learning joint representations of text, images, and point clouds. However, adopting poin…
ZeroGS: Training 3D Gaussian Splatting from Unposed Images
Yu Chen, Rolandos Alexandros Potamias, Evangelos Ververas +3
Neural radiance fields (NeRF) and 3D Gaussian Splatting (3DGS) are popular techniques to reconstruct and render photo-realistic images. However, the pre-requisite of running Struct…
Learning Precise Affordances from Egocentric Videos for Robotic Manipulation
Gen Li, Nikolaos Tsagkas, Jifei Song +4
Affordance, defined as the potential actions that an object offers, is crucial for embodied AI agents. For example, such knowledge directs an agent to grasp a knife by the handle f…
SAGS: Structure-Aware 3D Gaussian Splatting
Evangelos Ververas, Rolandos Alexandros Potamias, Jifei Song +2
Following the advent of NeRFs, 3D Gaussian Splatting (3D-GS) has paved the way to real-time neural rendering overcoming the computational burden of volumetric methods. Following th…
NCRF: Neural Contact Radiance Fields for Free-Viewpoint Rendering of Hand-Object Interaction
Zhongqun Zhang, Jifei Song, Eduardo Pérez-Pellitero +3
Modeling hand-object interactions is a fundamentally challenging task in 3D computer vision. Despite remarkable progress that has been achieved in this field, existing methods stil…
Deformable 3D Gaussian Splatting for Animatable Human Avatars
HyunJun Jung, Nikolas Brasch, Jifei Song +5
Recent advances in neural radiance fields enable novel view synthesis of photo-realistic images in dynamic settings, which can be applied to scenarios with human animation. Commonl…
SWinGS: Sliding Windows for Dynamic 3D Gaussian Splatting
Richard Shaw, Michal Nazarczuk, Jifei Song +4
Novel view synthesis has shown rapid progress recently, with methods capable of producing increasingly photorealistic results. 3D Gaussian Splatting has emerged as a promising meth…
Reality's Canvas, Language's Brush: Crafting 3D Avatars from Monocular Video
Yuchen Rao, Eduardo Perez Pellitero, Benjamin Busam +2
Recent advancements in 3D avatar generation excel with multi-view supervision for photorealistic models. However, monocular counterparts lag in quality despite broader applicabilit…
HeadGaS: Real-Time Animatable Head Avatars via 3D Gaussian Splatting
Helisa Dhamo, Yinyu Nie, Arthur Moreau +4
3D head animation has seen major quality and runtime improvements over the last few years, particularly empowered by the advances in differentiable rendering and neural radiance fi…
Human Gaussian Splatting: Real-time Rendering of Animatable Avatars
Arthur Moreau, Jifei Song, Helisa Dhamo +3
This work addresses the problem of real-time rendering of photorealistic human body avatars learned from multi-view videos. While the classical approaches to model and render virtu…
On the Importance of Accurate Geometry Data for Dense 3D Vision Tasks
HyunJun Jung, Patrick Ruhkamp, Guangyao Zhai +10
Learning-based methods to solve dense 3D vision problems typically train on 3D sensor data. The respectively used principle of measuring distances provides advantages and drawbacks…