1 citations · 1 across the 13 of their papers we have counts for
18 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…
Lite Any Stereo V2: Faster and Stronger Efficient Zero-Shot Stereo Matching
Junpeng Jing, Ronglai Zuo, Zhelun Shen +5
Recent advances in stereo matching have achieved remarkable accuracy, but often rely on large models, heavy computation, or additional foundation-model priors, making them difficul…
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…
HO-Flow: Generalizable Hand-Object Interaction Generation with Latent Flow Matching
Zerui Chen, Rolandos Alexandros Potamias, Shizhe Chen +3
Generating realistic 3D hand-object interactions (HOI) is a fundamental challenge in computer vision and robotics, requiring both temporal coherence and high-fidelity physical plau…
FreeScale: Scaling 3D Scenes via Certainty-Aware Free-View Generation
Chenhan Jiang, Yu Chen, Qingwen Zhang +4
The development of generalizable Novel View Synthesis (NVS) models is critically limited by the scarcity of large-scale training data featuring diverse and precise camera trajector…
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…
Egocentric Co-Pilot: Web-Native Smart-Glasses Agents for Assistive Egocentric AI
Sicheng Yang, Yukai Huang, Weitong Cai +8
What if accessing the web did not require a screen, a stable desk, or even free hands? For people navigating crowded cities, living with low vision, or experiencing cognitive overl…
Test-Time Scaling with Diffusion Language Models via Reward-Guided Stitching
Roy Miles, Aysim Toker, Andreea-Maria Oncescu +3
Reasoning with large language models often benefits from generating multiple chains-of-thought, but existing aggregation strategies are typically trajectory-level (e.g., selecting…
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…
Multilinear Mixture of Experts: Scalable Expert Specialization through Factorization
James Oldfield, Markos Georgopoulos, Grigorios G. Chrysos +5
The Mixture of Experts (MoE) paradigm provides a powerful way to decompose dense layers into smaller, modular computations often more amenable to human interpretation, debugging, a…