978 citations · 1.4k across the 10 of their papers we have counts for
11 papers
Pano3D: Unified 3D Reconstruction and Panoptic Segmentation
Victor Barberteguy, Ahmet Iscen, Mathilde Caron +3
Recent advances in 3D feedforward reconstruction neural networks have achieved remarkable success in dense reconstruction from images without any camera parameters. Yet, equipping…
Chapter-Llama: Efficient Chaptering in Hour-Long Videos with LLMs
Lucas Ventura, Antoine Yang, Cordelia Schmid +1
We address the task of video chaptering, i.e., partitioning a long video timeline into semantic units and generating corresponding chapter titles. While relatively underexplored, a…
Learning text-to-video retrieval from image captioning
Lucas Ventura, Cordelia Schmid, Gül Varol
We describe a protocol to study text-to-video retrieval training with unlabeled videos, where we assume (i) no access to labels for any videos, i.e., no access to the set of ground…
CoVR-2: Automatic Data Construction for Composed Video Retrieval
Lucas Ventura, Antoine Yang, Cordelia Schmid +1
Composed Image Retrieval (CoIR) has recently gained popularity as a task that considers both text and image queries together, to search for relevant images in a database. Most CoIR…
Scaling up sign spotting through sign language dictionaries
Gül Varol, Liliane Momeni, Samuel Albanie +2
The focus of this work is - given a video of an isolated sign, our task is to identify and it has been signed in a cont…
Towards unconstrained joint hand-object reconstruction from RGB videos
Yana Hasson, Gül Varol, Ivan Laptev +1
Our work aims to obtain 3D reconstruction of hands and manipulated objects from monocular videos. Reconstructing hand-object manipulations holds a great potential for robotics and…
Learning joint reconstruction of hands and manipulated objects
Yana Hasson, Gül Varol, Dimitrios Tzionas +4
Estimating hand-object manipulations is essential for interpreting and imitating human actions. Previous work has made significant progress towards reconstruction of hand poses and…
BodyNet: Volumetric Inference of 3D Human Body Shapes
Gül Varol, Duygu Ceylan, Bryan Russell +4
Human shape estimation is an important task for video editing, animation and fashion industry. Predicting 3D human body shape from natural images, however, is highly challenging du…
Learning from Synthetic Humans
Gül Varol, Javier Romero, Xavier Martin +4
Estimating human pose, shape, and motion from images and videos are fundamental challenges with many applications. Recent advances in 2D human pose estimation use large amounts of…
Long-term Temporal Convolutions for Action Recognition
Gül Varol, Ivan Laptev, Cordelia Schmid
Typical human actions last several seconds and exhibit characteristic spatio-temporal structure. Recent methods attempt to capture this structure and learn action representations w…
Hollywood in Homes: Crowdsourcing Data Collection for Activity Understanding
Gunnar A. Sigurdsson, Gül Varol, Xiaolong Wang +3
Computer vision has a great potential to help our daily lives by searching for lost keys, watering flowers or reminding us to take a pill. To succeed with such tasks, computer visi…