9 accepted papers
While image editing has advanced rapidly, video editing remains less explored, facing challenges in consistency, control, and generalization.We study the design space of data, architecture, and control, and introduce EasyV2V, a simple and effective framework for instruction-based video editing. On t
Multimodal Large Language Models (MLLMs) have demonstrated impressive 2D image/video understanding capabilities.However, there are no publicly standardized benchmarks to assess the abilities of MLLMs in understanding the 4D objects.In this paper, we introduce 4D-Bench, the first benchmark to evaluat…
Bimanual manipulation is crucial in robotics, enabling complex tasks in industrial automation and household services. However, it poses significant challenges due to the high-dimensional action space and intricate coordination requirements. While video prediction has been recently studied for repres…
Advancements in 3D Gaussian Splatting have significantly accelerated 3D reconstruction and generation. However it may require a large number of Gaussians which creates a substantial memory footprint. This paper introduces GES (Generalized Exponential Splatting) a novel representation that employs Ge…
We present ``Magic123'', a two-stage coarse-to-fine approach for high-quality, textured 3D mesh generation from a single image in the wild using *both 2D and 3D priors*. In the first stage, we optimize a neural radiance field to produce a coarse geometry. In the second stage, we adopt a memory-effic…
While diffusion models have shown impressive performance in 2D image/video generation, diffusion-based Text-to-Multi-view-Video (T2MVid) generation remains underexplored. The new challenges posed by T2MVid generation lie in the lack of massive captioned multi-view videos and the complexity of modeli…
With the recent advances in video and 3D understanding, novel 4D spatio-temporal methods fusing both concepts have emerged. Towards this direction, the Ego4D Episodic Memory Benchmark proposed a task for Visual Queries with 3D Localization (VQ3D). Given an egocentric video clip and an image crop dep…
PointNet++ is one of the most influential neural architectures for point cloud understanding. Although the accuracy of PointNet++ has been largely surpassed by recent networks such as PointMLP and Point Transformer, we find that a large portion of the performance gain is due to improved training str…
Weakly supervised object localization (WSOL) aims to localize object with only weak supervision like image-level labels. However, a long-standing problem for available techniques based on the classification network is that they often result in highlighting the most discriminative parts rather than t…