92 citations · 174 across the 13 of their papers we have counts for
13 papers
Orientation Matters: Making 3D Generative Models Orientation-Aligned
Yichong Lu, Yuzhuo Tian, Zijin Jiang +7
Humans intuitively perceive object shape and orientation from a single image, guided by strong priors about canonical poses. However, existing 3D generative models often produce mi…
Text2Immersion: Generative Immersive Scene with 3D Gaussians
Hao Ouyang, Kathryn Heal, Stephen Lombardi +1
We introduce Text2Immersion, an elegant method for producing high-quality 3D immersive scenes from text prompts. Our proposed pipeline initiates by progressively generating a Gauss…
DEYOv3: DETR with YOLO for Real-time Object Detection
Haodong Ouyang
Recently, end-to-end object detectors have gained significant attention from the research community due to their outstanding performance. However, DETR typically relies on supervis…
DEYOv2: Rank Feature with Greedy Matching for End-to-End Object Detection
Haodong Ouyang
This paper presents a novel object detector called DEYOv2, an improved version of the first-generation DEYO (DETR with YOLO) model. DEYOv2, similar to its predecessor, DEYOv2 emplo…
High-fidelity 3D GAN Inversion by Pseudo-multi-view Optimization
Jiaxin Xie, Hao Ouyang, Jingtan Piao +2
We present a high-fidelity 3D generative adversarial network (GAN) inversion framework that can synthesize photo-realistic novel views while preserving specific details of the inpu…
DEYO: DETR with YOLO for Step-by-Step Object Detection
Haodong Ouyang
Object detection is an important topic in computer vision, with post-processing, an essential part of the typical object detection pipeline, posing a significant bottleneck affecti…
Pretraining is All You Need for Image-to-Image Translation
Tengfei Wang, Ting Zhang, Bo Zhang +4
We propose to use pretraining to boost general image-to-image translation. Prior image-to-image translation methods usually need dedicated architectural design and train individual…
Real-Time Neural Character Rendering with Pose-Guided Multiplane Images
Hao Ouyang, Bo Zhang, Pan Zhang +5
We propose pose-guided multiplane image (MPI) synthesis which can render an animatable character in real scenes with photorealistic quality. We use a portable camera rig to capture…
Deep Video Prior for Video Consistency and Propagation
Chenyang Lei, Yazhou Xing, Hao Ouyang +1
Applying an image processing algorithm independently to each video frame often leads to temporal inconsistency in the resulting video. To address this issue, we present a novel and…
Internal Video Inpainting by Implicit Long-range Propagation
Hao Ouyang, Tengfei Wang, Qifeng Chen
We propose a novel framework for video inpainting by adopting an internal learning strategy. Unlike previous methods that use optical flow for cross-frame context propagation to in…
Image Inpainting with External-internal Learning and Monochromic Bottleneck
Tengfei Wang, Hao Ouyang, Qifeng Chen
Although recent inpainting approaches have demonstrated significant improvements with deep neural networks, they still suffer from artifacts such as blunt structures and abrupt col…
Neural Camera Simulators
Hao Ouyang, Zifan Shi, Chenyang Lei +2
We present a controllable camera simulator based on deep neural networks to synthesize raw image data under different camera settings, including exposure time, ISO, and aperture. T…
Human Pose Estimation with Spatial Contextual Information
Hong Zhang, Hao Ouyang, Shu Liu +4
We explore the importance of spatial contextual information in human pose estimation. Most state-of-the-art pose networks are trained in a multi-stage manner and produce several au…