25 citations · 30 across the 10 of their papers we have counts for
11 papers
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…
Dynamic Avatar-Scene Rendering from Human-centric Context
Wenqing Wang, Haosen Yang, Josef Kittler +1
Reconstructing dynamic humans interacting with real-world environments from monocular videos is an important and challenging task. Despite considerable progress in 4D neural render…
FAM Diffusion: Frequency and Attention Modulation for High-Resolution Image Generation with Stable Diffusion
Haosen Yang, Adrian Bulat, Isma Hadji +4
Diffusion models are proficient at generating high-quality images. They are however effective only when operating at the resolution used during training. Inference at a scaled reso…
FrozenSeg: Harmonizing Frozen Foundation Models for Open-Vocabulary Segmentation
Xi Chen, Haosen Yang, Sheng Jin +2
Open-vocabulary segmentation poses significant challenges, as it requires segmenting and recognizing objects across an open set of categories in unconstrained environments. Buildin…
Single Image, Any Face: Generalisable 3D Face Generation
Wenqing Wang, Haosen Yang, Josef Kittler +1
The creation of 3D human face avatars from a single unconstrained image is a fundamental task that underlies numerous real-world vision and graphics applications. Despite the signi…
AV-GS: Learning Material and Geometry Aware Priors for Novel View Acoustic Synthesis
Swapnil Bhosale, Haosen Yang, Diptesh Kanojia +2
Novel view acoustic synthesis (NVAS) aims to render binaural audio at any target viewpoint, given a mono audio emitted by a sound source at a 3D scene. Existing methods have propos…
Improving Gaussian Splatting with Localized Points Management
Haosen Yang, Chenhao Zhang, Wenqing Wang +4
Point management is critical for optimizing 3D Gaussian Splatting models, as point initiation (e.g., via structure from motion) is often distributionally inappropriate. Typically,…
Unsupervised Audio-Visual Segmentation with Modality Alignment
Swapnil Bhosale, Haosen Yang, Diptesh Kanojia +2
Audio-Visual Segmentation (AVS) aims to identify, at the pixel level, the object in a visual scene that produces a given sound. Current AVS methods rely on costly fine-grained anno…
Uncertainty-Aware Pseudo-Label Filtering for Source-Free Unsupervised Domain Adaptation
Xi Chen, Haosen Yang, Huicong Zhang +2
Source-free unsupervised domain adaptation (SFUDA) aims to enable the utilization of a pre-trained source model in an unlabeled target domain without access to source data. Self-tr…
Recognize Any Regions
Haosen Yang, Chuofan Ma, Bin Wen +3
Understanding the semantics of individual regions or patches of unconstrained images, such as open-world object detection, remains a critical yet challenging task in computer visio…
Leveraging Foundation models for Unsupervised Audio-Visual Segmentation
Swapnil Bhosale, Haosen Yang, Diptesh Kanojia +1
Audio-Visual Segmentation (AVS) aims to precisely outline audible objects in a visual scene at the pixel level. Existing AVS methods require fine-grained annotations of audio-mask…