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Found 16 papers, 8 papers with code
Diffusion Implicit Policy for Unpaired Scene-aware Motion Synthesis
Thus, we propose a unified framework, termed Diffusion Implicit Policy (DIP), for scene-aware motion synthesis, where paired motion-scene data are no longer necessary.
Textual Decomposition Then Sub-motion-space Scattering for Open-Vocabulary Motion Generation
For Textual Decomposition, we design a fine-grained description conversion algorithm, and combine it with the generalization ability of a large language model to convert any given motion text into atomic texts.
TIMotion: Temporal and Interactive Framework for Efficient Human-Human Motion Generation
For temporal modeling, the single-person-based methods concatenate two people into a single one directly, while the separate modeling-based methods skip the modeling of interaction sequences.
Adaptive Slot Attention: Object Discovery with Dynamic Slot Number
Moreover, our analysis substantiates that our method exhibits the capability to dynamically adapt the slot number according to each instance's complexity, offering the potential for further exploration in slot attention research.
FreeMotion: A Unified Framework for Number-free Text-to-Motion Synthesis
Text-to-motion synthesis is a crucial task in computer vision.
Ranked #5 on
Motion Synthesis
on InterHuman
Learning Topology Uniformed Face Mesh by Volume Rendering for Multi-view Reconstruction
Our goal is to leverage the superiority of neural volume rendering into multi-view reconstruction of face mesh with consistent topology.
SDPose: Tokenized Pose Estimation via Circulation-Guide Self-Distillation
To mitigate the problem of under-fitting, we design a transformer module named Multi-Cycled Transformer(MCT) based on multiple-cycled forwards to more fully exploit the potential of small model parameters.
Make-It-Vivid: Dressing Your Animatable Biped Cartoon Characters from Text
Creating and animating 3D biped cartoon characters is crucial and valuable in various applications.
Repositioning the Subject within Image
To assess SEELE's effectiveness in subject repositioning, we assemble a real-world subject repositioning dataset called ReS.
Ranked #2 on
Image Inpainting
on Places2
Test-Time Linear Out-of-Distribution Detection
We conduct a thorough investigation theoretically and empirically to analyze and understand the meaning of such a linear trend in OOD detection.
Out-of-Distribution Detection
Out of Distribution (OOD) Detection
+1
Rethinking Amodal Video Segmentation from Learning Supervised Signals with Object-centric Representation
Furthermore, we propose a multi-view fusion layer based temporal module which is equipped with a set of object slots and interacts with features from different views by attention mechanism to fulfill sufficient object representation completion.
Unsupervised Open-Vocabulary Object Localization in Videos
In this paper, we show that recent advances in video representation learning and pre-trained vision-language models allow for substantial improvements in self-supervised video object localization.
RFENet: Towards Reciprocal Feature Evolution for Glass Segmentation
Glass-like objects are widespread in daily life but remain intractable to be segmented for most existing methods.
A Simple Test-Time Method for Out-of-Distribution Detection
In contrast, this paper proposes a simple Test-time Linear Training (ETLT) method for OOD detection.
Out-of-Distribution Detection
Out of Distribution (OOD) Detection
Clustering by the Probability Distributions from Extreme Value Theory
In contrast, the GPD fits the distribution of distance to the centroid exceeding a sufficiently large threshold, leading to a more stable performance of GPD k-means.
An Improved Composite Functional Gradient Learning by Wasserstein Regularization for Generative adversarial networks
However, the discriminator using logistic regression from the CFG framework is gradually hard to discriminate between real and fake images while the training steps go on.
