7 papers
OmniGF: A Dual-Branch Vision-Language Framework for Unified Gaze Following
Qiaomu Miao, Haoyu Wu, Jingyi Xu +2
Understanding human gaze behavior is essential for complex scene comprehension and human-computer interaction. Traditional gaze following models are typically restricted to pure sp…
Learning 3D Reconstruction with Priors in Test Time
Lei Zhou, Haoyu Wu, Akshat Dave +1
We introduce a test-time framework for multiview Transformers (MVTs) that incorporates priors (e.g., camera poses, intrinsics, and depth) to improve 3D tasks without retraining or…
Phase-Aligned RoPE for Mixed-Resolution Diffusion Transformer
Haoyu Wu, Jingyi Xu, Qiaomu Miao +2
Rotary positional embeddings (RoPE) are widely used in diffusion transformers (DiTs) to encode spatial relationships, yet their behavior with mixed-resolution tokens remains undere…
Multi-view Gaze Target Estimation
Qiaomu Miao, Vivek Raju Golani, Jingyi Xu +3
This paper presents a method that utilizes multiple camera views for the gaze target estimation (GTE) task. The approach integrates information from different camera views to impro…
MLI-NeRF: Multi-Light Intrinsic-Aware Neural Radiance Fields
Yixiong Yang, Shilin Hu, Haoyu Wu +3
Current methods for extracting intrinsic image components, such as reflectance and shading, primarily rely on statistical priors. These methods focus mainly on simple synthetic sce…
Direct and Explicit 3D Generation from a Single Image
Haoyu Wu, Meher Gitika Karumuri, Chuhang Zou +4
Current image-to-3D approaches suffer from high computational costs and lack scalability for high-resolution outputs. In contrast, we introduce a novel framework to directly genera…
Importance-Based Token Merging for Efficient Image and Video Generation
Haoyu Wu, Jingyi Xu, Hieu Le +1
Token merging can effectively accelerate various vision systems by processing groups of similar tokens only once and sharing the results across them. However, existing token groupi…