Search Results for author:
Found 31 papers, 12 papers with code
PromptFusion: Decoupling Stability and Plasticity for Continual Learning
Such a trade-off is referred to as the stabilityplasticity dilemma and is a more general and challenging problem for continual learning.
Human MotionFormer: Transferring Human Motions with Vision Transformers
In this paper, we propose Human MotionFormer, a hierarchical ViT framework that leverages global and local perceptions to capture large and subtle motion matching, respectively.
One Model to Edit Them All: Free-Form Text-Driven Image Manipulation with Semantic Modulations
Based on the visual latent space of StyleGAN[21] and text embedding space of CLIP[34], studies focus on how to map these two latent spaces for text-driven attribute manipulations.
ObjectFormer for Image Manipulation Detection and Localization
Recent advances in image editing techniques have posed serious challenges to the trustworthiness of multimedia data, which drives the research of image tampering detection.
Action-guided 3D Human Motion Prediction
The ability of forecasting future human motion is important for human-machine interaction systems to understand human behaviors and make interaction.
Fine-Grained Shape-Appearance Mutual Learning for Cloth-Changing Person Re-Identification
Recently, person re-identification (Re-ID) has achieved great progress.
Ranked #3 on
Person Re-Identification
on PRCC
PD-GAN: Probabilistic Diverse GAN for Image Inpainting
To this end, we propose spatially probabilistic diversity normalization (SPDNorm) inside the modulation to model the probability of generating a pixel conditioned on the context information.
M2TR: Multi-modal Multi-scale Transformers for Deepfake Detection
The widespread dissemination of Deepfakes demands effective approaches that can detect perceptually convincing forged images.
Few-Shot Human Motion Transfer by Personalized Geometry and Texture Modeling
We present a new method for few-shot human motion transfer that achieves realistic human image generation with only a small number of appearance inputs.
DeFLOCNet: Deep Image Editing via Flexible Low-level Controls
While existing methods combine an input image and these low-level controls for CNN inputs, the corresponding feature representations are not sufficient to convey user intentions, leading to unfaithfully generated content.
Learning 3D Face Reconstruction with a Pose Guidance Network
We present a self-supervised learning approach to learning monocular 3D face reconstruction with a pose guidance network (PGN).
MakeItTalk: Speaker-Aware Talking-Head Animation
We present a method that generates expressive talking heads from a single facial image with audio as the only input.
Channel Interaction Networks for Fine-Grained Image Categorization
Fine-grained image categorization is challenging due to the subtle inter-class differences. We posit that exploiting the rich relationships between channels can help capture such differences since different channels correspond to different semantics.
Ranked #20 on
Fine-Grained Image Classification
on FGVC Aircraft
iFAN: Image-Instance Full Alignment Networks for Adaptive Object Detection
We propose Image-Instance Full Alignment Networks (iFAN) to tackle this problem by precisely aligning feature distributions on both image and instance levels: 1) Image-level alignment: multi-scale features are roughly aligned by training adversarial domain classifiers in a hierarchically-nested fashion.
FiNet: Compatible and Diverse Fashion Image Inpainting
The latent representations are jointly optimized with the corresponding generation network to condition the synthesis process, encouraging a diverse set of generated results that are visually compatible with existing fashion garments.
ClothFlow: A Flow-Based Model for Clothed Person Generation
By estimating a dense flow between source and target clothing regions, ClothFlow effectively models the geometric changes and naturally transfers the appearance to synthesize novel images as shown in Figure 1.
Ranked #6 on
Virtual Try-on
on VITON
(SSIM metric)
Multi-Similarity Loss with General Pair Weighting for Deep Metric Learning
A family of loss functions built on pair-based computation have been proposed in the literature which provide a myriad of solutions for deep metric learning.
Ranked #4 on
Image Retrieval
on In-Shop
Compatible and Diverse Fashion Image Inpainting
The latent representations are jointly optimized with the corresponding generation network to condition the synthesis process, encouraging a diverse set of generated results that are visually compatible with existing fashion garments.
Generate, Segment and Refine: Towards Generic Manipulation Segmentation
The advent of image sharing platforms and the easy availability of advanced photo editing software have resulted in a large quantities of manipulated images being shared on the internet.
Learning Rich Features for Image Manipulation Detection
Image manipulation detection is different from traditional semantic object detection because it pays more attention to tampering artifacts than to image content, which suggests that richer features need to be learned.
Enhancing HEVC Compressed Videos with a Partition-masked Convolutional Neural Network
In this paper, we propose a partition-masked Convolution Neural Network (CNN) to achieve compressed-video enhancement for the state-of-the-art coding standard, High Efficiency Video Coding (HECV).
Multimedia
DCAN: Dual Channel-wise Alignment Networks for Unsupervised Scene Adaptation
In particular, given an image from the source domain and unlabeled samples from the target domain, the generator synthesizes new images on-the-fly to resemble samples from the target domain in appearance and the segmentation network further refines high-level features before predicting semantic maps, both of which leverage feature statistics of sampled images from the target domain.
Two-Stream Neural Networks for Tampered Face Detection
We propose a two-stream network for face tampering detection.
VITON: An Image-based Virtual Try-on Network
We present an image-based VIirtual Try-On Network (VITON) without using 3D information in any form, which seamlessly transfers a desired clothing item onto the corresponding region of a person using a coarse-to-fine strategy.
NISP: Pruning Networks using Neuron Importance Score Propagation
In contrast, we argue that it is essential to prune neurons in the entire neuron network jointly based on a unified goal: minimizing the reconstruction error of important responses in the "final response layer" (FRL), which is the second-to-last layer before classification, for a pruned network to retrain its predictive power.
Automatic Spatially-aware Fashion Concept Discovery
This paper proposes an automatic spatially-aware concept discovery approach using weakly labeled image-text data from shopping websites.
Learning Fashion Compatibility with Bidirectional LSTMs
To this end, we propose to jointly learn a visual-semantic embedding and the compatibility relationships among fashion items in an end-to-end fashion.
Son of Zorn's Lemma: Targeted Style Transfer Using Instance-aware Semantic Segmentation
This work considers targeted style transfer, in which the style of a template image is used to alter only part of a target image.
VRFP: On-the-fly Video Retrieval using Web Images and Fast Fisher Vector Products
VRFP is a real-time video retrieval framework based on short text input queries, which obtains weakly labeled training images from the web after the query is known.
Selecting Relevant Web Trained Concepts for Automated Event Retrieval
Given a text description of an event, event retrieval is performed by selecting concepts linguistically related to the event description and fusing the concept responses on unseen videos.
Tree-based Visualization and Optimization for Image Collection
The visualization of an image collection is the process of displaying a collection of images on a screen under some specific layout requirements.
