activity
20202026
most citedEgo-Exo4D: Understanding Skilled Human Activity from First- and Third-Person Perspectives

20 citations · 23 across the 14 of their papers we have counts for

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14 papers · 1 filter

cs.CV2026

Personal Visual Context Learning in Large Multimodal Models

Zihui Xue, Ami Baid, Sangho Kim +2

As wearable devices like smart glasses integrate Large Multimodal Models (LMMs) into the continuous first-person visual streams of individual users, the evolution of these models i…

cs.CV2026

Don't Let the Video Speak: Audio-Contrastive Preference Optimization for Audio-Visual Language Models

Ami Baid, Zihui Xue, Kristen Grauman

While Audio-Visual Language Models (AVLMs) have achieved remarkable progress over recent years, their reliability is bottlenecked by cross-modal hallucination. A particularly perva…

cs.CV2025

Seeing without Pixels: Perception from Camera Trajectories

Zihui Xue, Kristen Grauman, Dima Damen +2

Can one perceive a video's content without seeing its pixels, just from the camera trajectory-the path it carves through space? This paper is the first to systematically investigat…

cs.CV2025

When Thinking Drifts: Evidential Grounding for Robust Video Reasoning

Mi Luo, Zihui Xue, Alex Dimakis +1

Video reasoning, the task of enabling machines to infer from dynamic visual content through multi-step logic, is crucial for advanced AI. While the Chain-of-Thought (CoT) mechanism…

cs.CV2025

Seeing the Arrow of Time in Large Multimodal Models

Zihui Xue, Mi Luo, Kristen Grauman

The Arrow of Time (AoT)-time's irreversible flow shaping physical events-is fundamental to video comprehension, yet remains a significant challenge for modern large multimodal mode…

cs.CV2025

SPOC: Spatially-Progressing Object State Change Segmentation in Video

Priyanka Mandikal, Tushar Nagarajan, Alex Stoken +2

Object state changes in video reveal critical cues about human and agent activity. However, existing methods are limited to temporal localization of when the object is in its initi…

cs.CV2025

REG: Rectified Gradient Guidance for Conditional Diffusion Models

Zhengqi Gao, Kaiwen Zha, Tianyuan Zhang +2

Guidance techniques are simple yet effective for improving conditional generation in diffusion models. Albeit their empirical success, the practical implementation of guidance dive…

cs.CV2024

Progress-Aware Video Frame Captioning

Zihui Xue, Joungbin An, Xitong Yang +1

While image captioning provides isolated descriptions for individual images, and video captioning offers one single narrative for an entire video clip, our work explores an importa…

cs.CV2024

Action2Sound: Ambient-Aware Generation of Action Sounds from Egocentric Videos

Changan Chen, Puyuan Peng, Ami Baid +4

Generating realistic audio for human actions is important for many applications, such as creating sound effects for films or virtual reality games. Existing approaches implicitly a…

cs.CV2024

HOI-Swap: Swapping Objects in Videos with Hand-Object Interaction Awareness

Zihui Xue, Mi Luo, Changan Chen +1

We study the problem of precisely swapping objects in videos, with a focus on those interacted with by hands, given one user-provided reference object image. Despite the great adva…

cs.CV2024★ 1 cited

Put Myself in Your Shoes: Lifting the Egocentric Perspective from Exocentric Videos

Mi Luo, Zihui Xue, Alex Dimakis +1

We investigate exocentric-to-egocentric cross-view translation, which aims to generate a first-person (egocentric) view of an actor based on a video recording that captures the act…

cs.CV2024

Detours for Navigating Instructional Videos

Kumar Ashutosh, Zihui Xue, Tushar Nagarajan +1

We introduce the video detours problem for navigating instructional videos. Given a source video and a natural language query asking to alter the how-to video's current path of exe…

cs.CV2023★ 2 cited

Learning Object State Changes in Videos: An Open-World Perspective

Zihui Xue, Kumar Ashutosh, Kristen Grauman

Object State Changes (OSCs) are pivotal for video understanding. While humans can effortlessly generalize OSC understanding from familiar to unknown objects, current approaches are…

cs.CV2023★ 20 cited

Ego-Exo4D: Understanding Skilled Human Activity from First- and Third-Person Perspectives

Kristen Grauman, Andrew Westbury, Lorenzo Torresani +98

We present Ego-Exo4D, a diverse, large-scale multimodal multiview video dataset and benchmark challenge. Ego-Exo4D centers around simultaneously-captured egocentric and exocentric…