Search Results for author:
Found 37 papers, 10 papers with code
IPAD: Industrial Process Anomaly Detection Dataset
Video anomaly detection (VAD) is a challenging task aiming to recognize anomalies in video frames, and existing large-scale VAD researches primarily focus on road traffic and human activity scenes.
Infusion: Preventing Customized Text-to-Image Diffusion from Overfitting
Text-to-image (T2I) customization aims to create images that embody specific visual concepts delineated in textual descriptions.
Rethinking Clothes Changing Person ReID: Conflicts, Synthesis, and Optimization
However, such improvement sacrifices the performance under the standard protocol, caused by the inner conflict between standard and CC.
Monocular Identity-Conditioned Facial Reflectance Reconstruction
We first learn a high-quality prior for facial reflectance.
ReGenNet: Towards Human Action-Reaction Synthesis
Humans constantly interact with their surrounding environments.
A Comparative Study of Perceptual Quality Metrics for Audio-driven Talking Head Videos
However, performance evaluation research lags behind the development of talking head generation techniques.
Inter-X: Towards Versatile Human-Human Interaction Analysis
We also equip Inter-X with versatile annotations of more than 34K fine-grained human part-level textual descriptions, semantic interaction categories, interaction order, and the relationship and personality of the subjects.
SingingHead: A Large-scale 4D Dataset for Singing Head Animation
Extensive comparative experiments with both SOTA 3D facial animation and 2D portrait animation methods demonstrate the necessity of singing-specific datasets in singing head animation tasks and the promising performance of our unified facial animation framework.
EvaSurf: Efficient View-Aware Implicit Textured Surface Reconstruction on Mobile Devices
In our method, we first employ an efficient surface-based model with a multi-view supervision module to ensure accurate mesh reconstruction.
Generalizable Person Search on Open-world User-Generated Video Content
Person search is a challenging task that involves detecting and retrieving individuals from a large set of un-cropped scene images.
Directional Texture Editing for 3D Models
However, the inherent complexity of 3D models and the ambiguous text description lead to the challenge in this task.
HyperStyle3D: Text-Guided 3D Portrait Stylization via Hypernetworks
While the use of 3D-aware GANs bypasses the requirement of 3D data, we further alleviate the necessity of style images with the CLIP model being the stylization guidance.
GANHead: Towards Generative Animatable Neural Head Avatars
To bring digital avatars into people's lives, it is highly demanded to efficiently generate complete, realistic, and animatable head avatars.
Head3D: Complete 3D Head Generation via Tri-plane Feature Distillation
Head generation with diverse identities is an important task in computer vision and computer graphics, widely used in multimedia applications.
Improving Fairness in Facial Albedo Estimation via Visual-Textual Cues
Our key insight is that intrinsic semantic attributes such as race, skin color, and age can constrain the albedo map.
3D-Aware Face Swapping
To achieve this, we take advantage of the strong geometry and texture prior of 3D human faces, where the 2D faces are projected into the latent space of a 3D generative model.
Domain Adaptive Person Search
In this paper, we take a further step and present Domain Adaptive Person Search (DAPS), which aims to generalize the model from a labeled source domain to the unlabeled target domain.
DialogueNeRF: Towards Realistic Avatar Face-to-Face Conversation Video Generation
In this paper, we propose a novel unified framework based on neural radiance field (NeRF) to address this task.
ActFormer: A GAN-based Transformer towards General Action-Conditioned 3D Human Motion Generation
We present a GAN-based Transformer for general action-conditioned 3D human motion generation, including not only single-person actions but also multi-person interactive actions.
A Coding Framework and Benchmark towards Compressed Video Understanding
However, in real-world scenarios, the videos are first compressed before the transportation and then decompressed for understanding.
DFA-NeRF: Personalized Talking Head Generation via Disentangled Face Attributes Neural Rendering
Specifically, neural radiance field takes lip movements features and personalized attributes as two disentangled conditions, where lip movements are directly predicted from the audio inputs to achieve lip-synchronized generation.
MovieNet-PS: A Large-Scale Person Search Dataset in the Wild
Person search aims to jointly localize and identify a query person from natural, uncropped images, which has been actively studied over the past few years.
Ranked #3 on
Person Search
on CUHK-SYSU
TAL: Two-stream Adaptive Learning for Generalizable Person Re-identification
In the meantime, we design an adaptive BN layer in the domain-invariant stream, to approximate the statistics of various unseen domains.
Domain Generalization
Generalizable Person Re-identification
+1
Efficient Person Search: An Anchor-Free Approach
Third, by investigating the advantages of both anchor-based and anchor-free models, we further augment AlignPS with an ROI-Align head, which significantly improves the robustness of re-id features while still keeping our model highly efficient.
Ranked #4 on
Person Search
on PRW
EAN: Event Adaptive Network for Enhanced Action Recognition
In this paper, we propose a unified action recognition framework to investigate the dynamic nature of video content by introducing the following designs.
Ranked #14 on
Action Recognition
on Something-Something V1
Local-to-Global Self-Attention in Vision Transformers
Transformers have demonstrated great potential in computer vision tasks.
Exploring Visual Context for Weakly Supervised Person Search
This paper inventively considers weakly supervised person search with only bounding box annotations.
Learning Multi-Granular Hypergraphs for Video-Based Person Re-Identification
In each hypergraph, different temporal granularities are captured by hyperedges that connect a set of graph nodes (i. e., part-based features) across different temporal ranges.
Ranked #6 on
Person Re-Identification
on iLIDS-VID
Learning Multi-Attention Context Graph for Group-Based Re-Identification
Extensive experiments on the novel dataset as well as three existing datasets clearly demonstrate the effectiveness of the proposed framework for both group-based re-id tasks.
Anchor-Free Person Search
Person search aims to simultaneously localize and identify a query person from realistic, uncropped images, which can be regarded as the unified task of pedestrian detection and person re-identification (re-id).
Ranked #10 on
Person Search
on CUHK-SYSU
Learning Context Graph for Person Search
Person re-identification has achieved great progress with deep convolutional neural networks.
Pose Transferrable Person Re-Identification
On the other hand, in addition to the conventional discriminator of GAN (i. e., to distinguish between REAL/FAKE samples), we propose a novel guider sub-network which encourages the generated sample (i. e., with novel pose) towards better satisfying the ReID loss (i. e., cross-entropy ReID loss, triplet ReID loss).
Skeleton-aided Articulated Motion Generation
This work make the first attempt to generate articulated human motion sequence from a single image.
Ranked #2 on
Gesture-to-Gesture Translation
on NTU Hand Digit
Image Matching via Loopy RNN
Towards this end, we propose a novel loopy recurrent neural network (Loopy RNN), which is capable of aggregating relationship information of two input images in a progressive/iterative manner and outputting the consolidated matching score in the final iteration.
Depth Structure Preserving Scene Image Generation
Key to automatically generate natural scene images is to properly arrange among various spatial elements, especially in the depth direction.
Predicting Human Interaction via Relative Attention Model
Predicting human interaction is challenging as the on-going activity has to be inferred based on a partially observed video.
Person Re-Identification via Recurrent Feature Aggregation
We address the person re-identification problem by effectively exploiting a globally discriminative feature representation from a sequence of tracked human regions/patches.
